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by: Melisa O'Reilly


Melisa O'Reilly
GPA 3.54


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Class Notes
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This 61 page Class Notes was uploaded by Melisa O'Reilly on Saturday September 12, 2015. The Class Notes belongs to Arts 1 at University of California - Irvine taught by Staff in Fall. Since its upload, it has received 31 views. For similar materials see /class/201956/arts-1-university-of-california-irvine in Arts at University of California - Irvine.

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Date Created: 09/12/15
MindBody Overview 1 Physics and Folk Psychology a Physics hardnosed particles observables repeatable b Folk Psychology Beliefs hopes desires sensations subjective consciousness 2 Issues a Ontological 1 What are mental states and processes 2 What are physical states and processes 3 How are the mental and physical related 4 Example Replace NS with silicon starting at retina Still conscious b Semantical 1 Where do propositional attitudes get their meanings EX Belief Belief that p 2 Where do qualia get their meanings EX pain red warmth 3 Where do other terms get their meanings EX horse electron c Epistemological 1 How do we know anything 2 How do we know if something has a mind Problem of other minds 3 How do I know my own mental states Problem of selfconsciousness d Methodological 1 What are appropriate methods for studying psychology 2 What determines their propriety 3 Ontologies a Substance Dualism 1 Descartes Mind is a distinct substance from matter 2 Matter extended in space has length width breadth and position 1 3 Mind essence is thinking has no extension or position in space 4 Reasons how could matter ever use language or reason mathematically 5 Problem How can mind interact with matter and not violate conservation laws 6 Problem Electrons have no extension or determinate postion in space Yet physical 7 Eccles and Popper mind affects probabilities of exocytosis at all synapses b Popular Duulisrn 1 Mind is a ghost in a machine machinebody mindspiritual substance 2 Mind is inside body probably brain 3 Mind interacts with brain by some form of energy exchange 4 Advantage survival of bodily death 5 Problem not a precise theory c Property Duulisrn 1 Brain certain complex systems have special properties like in tune guitar 2 Properties are not reducible to physical properties try to reduce money 3 Epiphenomenalism mind emerges from brain but has no causal effects 4 lnteractionist Mind emerges but causally affects brain 5 Elementalproperty dualism mental is fundaInental property like mass charge etc o Arguments For Duulisrn 1 Religious backing 2 Introspective plausibility 3 lrreducibility of the mental o Arguments Against Duulisrn l Ockhaln s Razor 2 Explanatory i1npotence 3 Psychological de cits from brain damage 4 Argument from evolution start simple mindless evolve to complex with mind 9 D Dh Logical Behaviorism l Psychological talk is a shorthand for complex behaviors 2 Analysis by dispositions Thirsty If water would drink says thirsty etc Arguments Against Behaviorism l lgnores qualia and inner experience 2 Could never specify the dispositions infinitely long Identity Theory Reductive Materialism 1 Mental states just are brain states 2 Type physicalism All properties the sciences study are physical properties 3 lntertheoretic Reduction 4 TN reduces To if TN plus boundary conditions yields MO isomorphic to To Arguments For Identity Theory 1 We are purely physical beings start from fertilized egg and accrete molecules 2 Argument from evolutionary history 3 Neural dependence of all known mental phenomena 4 Success of neurosciences in explaining behavioral capacities and deficits Arguments Against Identity Theory 1 How could mental states be brain states Love 40 Hz of left li1nbic lobe 2 Mistakes symbol for reality Brain is symbolic construct of perception 3 Requires mental properties to be physical Too strong Take money exaInple again 4 Nothing without brain can have mentation What about silicon creatures from Mars Funetionalism 1 Mental states defined by causal relations of l stimuli 2 behavior 3 mental states 2 Ex Headache Groans beliefs about aspirin take aspirin avoid bright light etc 3 Ex Turing coke machine 4 Difference with behaviorism Admits causal interactions of mental states 3 OF Fquot 5 Difference with identity theory only says mental tokenphysical token not type 6 Token physicalism All events the sciences study are physical events 7 Allows minds to be in computers not just brains 8 Grants the autonomy of psychology relative to physics 9 Psychology has own irreducible laws and subject matter Arguments Against Funetionalism l Spectruln inversion argument 2 Absent qualia problem Block s Chinese simulation of mind using 109 people Eliminative Materialism 1 Folk psychology is a false theory and will be elilninated in favor of neuro science 2 Ex caloric phlogiston starry sphere of the heavens 3 Learn to interpret our experiences neurally l have a 40 Hz limbic oscilla tion Arguments For Eliminative Materialism l Explanatory failures of folk psychology Why sleep How learn Mental illness 2 Many other folk theories have been wrong folk physics impetus earth center 3 Folk psychology has not improved much in over 2000 years 3 Reducing folk psych to neuroscience is demanding elimination is more likely Arguments Against Eliminative Materialism l lntrospection does not reveal neural states only psychological states 2 How shall we believe elilninative materialism if we eliminate beliefs 3 Folk psych is powerful revised not eliminated Ex invited to talk in LA Idealism 1 Berkeley Physical objects don t exist unperceived ideas in the mind 2 Kant Mind s knows itself mediately like it knows the world 4 T 39s39ts 39o39f Gauss39iah39lit39y V quot 39OlivierivDoir C I T A I amp Princeton University 39 for the WMAP scienceteam WMAP Science Team Why testing iQt Gaussianity in the ttest plaice3 IThe detailed statistical analysis of this map yield exquisite cosmological information IBut the hypothesis that the analyzed signal is GaussianIsotropic is a key hypothesis in the analysis Ilt enters both at the power spectrum measurement level and at the cosmological parameter measurement level Ilt has to be tested quot The observed sky is NC What we really do is testing for residual NC so extra care is appropriate Well known astrophysical sources Point sources extra galactic point sources resolved or unresolved t3 Galactic emission Secondary anisotropies known to exist Lensing Ll SZ Observational effects inhomogeneous noise mild noise correlation Unknown Primordial signal the real science driver If Inflation fNLlt1 but curvaton inflation or ghost inflation for example can have fNL1OO Limit after WMAP l is 54ltfNLlt134 95 A A 2 A Cplx x fNL x G Non trivial topology most of models ruled out after yearl V Topological Defects Unknown andor unaccounted for physics Outline We performed various statistical tests using 3 year KKaHaDust template cleaned maps 1 point probability function Minkowsky functionals 3 points probability function in real and harmonic space 4 points probability function in real space Large scale modulation 1 point probability function Number of observations per pixel 10275 Nobs Logarithmic 103 7 I The noise is inhomogeneous over the slq I A simple pdf of the data would lead to a nonzero kurtosis at scales Where the noise is non negligible Testing Gaussianity pdf distribution We consider a field which a quotlocal variance normalized temperature field poor man s whitened map Red line is Gaussian pdf of unit variance No fit involved Kp2 mask Very good agreement Minkowski lunc rionala IWeII de ned ma iema cal functions rim measure the number length and area of an excursion set define Sm a given threshold v lWell defined analytical prediction a Gaussian field or a mildly nanGaussian field IErrots and predictions are obtained with simulations ham to account for the inhmogeneous noise l 739 ill quot 39 39 M 39 3 Comparison quotquot39 39 39 a a Residuals l mmma w to simulations correlated lll Ml it 3 9 It Maud v e Res 1 28 pix r HVW mm KpO masking w mm is o I Muses v uncmm Is sith acame Xi 52warz gm mggl PgMA ha I Tahhllxafuk nkm m vlammnmmmmmw g DOF Sm FwaiESP 399 15 154 my 193 15 1amp1 Q1 1441 151 153 Q54 514 5 1133 0 31 1amp3 13 1amp9 1332 m3 1 H9 4 13 155 54111 45 4322 11 15 15A Em m 153 Sa 15 15 3 422 4amp1 282 152 153 1910 L5 15 141 15 1amp8 m 451 491 193 13 1amp5 13 151 l 2amp3 15 1M Chmhimd 1am if 4amp0 PM 1 1 1 128 64 4 186 M 32 33 32 32 113 123 la 16 3 g 8 8 Comparison to NC simulations allows to constrain fNL I 7i66 6800 Bispectrum i The bispectrum is sensitive to both primordial NC but also varsious sources of secondary anisotropies SZ lensing 7 V 717 f Statistical properties relatively well understood The bispectrum measures phases correlation ofT fluctuation 1 d Sprimardial 4nr2dr nAr7 Bzrv fsky 4TB Measure the skewness of te m p e r at u r e m a p AG 13 2 a r yjlC PM Bispectrum quotselection weighted in harmonic function space Br7 2 5 r 7 Cl lglmlflm 0 7 fdlgn 1 5 rfdlPkng kj kr Statistic optimized to pick up the fNL contribution to the Bardeen potential Demonstrated on simulations to be unbiased 61 r Bispectrum The ltering of the map can also be optimized to detect point source contribution M 3 see 4KD1 bee 1 DO 261me CMB withened map m 7Whie we used to consider Max265 we now consider Max350 VEWe 0 lain 39 e instead of 758ltfmlt 137 for year 1 v 39 c 39 39 39 39 amplitude 39 w c w other estimates Testing Gaussianity 4 points function IClaims of large scale deviation from Gaussianity on large scales but no 3 point signal ICould we have a N6 signal without a 3 point bispectrum signal lYes if eg Bardeen curvature potential can be written as 130 ltlgt3l1gNLII3l I The optimal estimator can be written as G 2 Z TprZTpf N132 9 Testing Gaussianity 4 points function V m C I 2 2 o a 3 U U 9 9 E E D D 3 5 31 1 20 025 9 i V and W shows no evidence for any non trivial four point function 3 Q deviation very likely due to point sources At the level of WMAP 3year data there are no significant cosmological or systematic effect varying the field on large scales CPO W l1 gNLllf ll Testing Caussiianity Large scale temperature fluctuatiiens I Low I alignments Tegmark et al 04 de Oliveira7Costa et 3 O4 Eriksen et al 04 Copi et al 04 Land amp Mageuijo O4 3 I Low I power alignment probability was estimated at 4t10 0 This result is a posteriori so potentially strongly biased but also potentially significant Testing Gaussianiity Large scale temperature fluctuations IPower asymmetry north W l2 34 south Mr l2 34 Eriksen et al 03 Hlansen H a 03 0Map of R for coordinate system pole centered in Souradeep et al 03 did notfind this each Circle N100 circle 0Plane of maximum asymmetry appears to be closed to ecliptic plane K I Low COBEWMAP quadrupole 2 Efstathiou 04 ii a Slozar et al 04 02 Bielewicz et al 04 When accounting for the full likelihood shape likelihood is about 15 Unchanged Tempemure maps an large scales 9 a 4 9 year lrpub year 3 year 3 7 year 1 Q wma I I 72m 1m 2m The previously mentioned analysis are very unlikely to be altered ran run an Testing Isotropy Large scale modulation We Chane to address these 3 issues in a unifymg manner by asking a simple question Can we describe the Observed temperature field as a Gaussian isotropic fied T modulated by an arbitrary deterministic fied f 9 TO T l1f l Although the theoretical motivations are still weak this phenomenological description is appealing since we can address and quantify in a Bayesian context the alignment low I power and asymmetry simultaneously f 0 is the usual assumption If f was dipolar it could lead to an asymmetry and potentially to some modifications to C of T If f was quadrupolar it would tend to align the observed quadrupole and octopole independantly ofT and alter the C I ietc39 1 0r 2 50 We can compute the exact likelihood L l C f 7 m Testing Gausslamly Laure scale MOldlUlMtlllO IAssuming this description 0f the observed eld t m an T 1 13 mm 3 Z Imam 1 35 awe can cumpute exactly in map space 1 mg Tm Weth 31f an Millie 32 a 9 Cquot1 31 where mam E 2 IQgPd km 6 I Computing this likelihood in real Space at res 3 is fast enough so that we can solve simultaanle for the ML films and CIS RI 7 using a MCMC solvar IExaCt handling 9f the mask ITested on simulations where an arbitrary f was applied lApplied to Q V and W leaned maps separately 1D mavginahzed 26mg 1D mmjmalized 05 22 v77 J Imml but similar for Imax2 iestingCarrssianity targesealemedrrlatien iiiite i ttitir iii Signi cance t1 Dipeiarmeduiatien tart Ai iln i34ier3ertra parameters ti Quadrupelar inert Aiiin i 80ier 8 extra parameters rtiireewiQaareunaiieetedasarethemuitipelemedereii trNetethatweeeuideaaiirbeeattheaigniieaneewereweteeheereaperterieriadireetienbutnephyrieal matiratienareiar r iWe eeneiudethat more evidence are required ier sucharadiealreinterpretatien at our data Conclusions v Vznou Lu pom tzumcx 3 Mmkokayiuncuonzk None ohhe above bad 0 a Mgmhcznt dewauonnom gammy ov Xotvopy M my mpvoved om ve ezxe am am u ta k wmonow yvryvl m m any NE arm ym C ezned map Home ovznznce mamas ave aH aw zb e horn Lambda We ave ookmgmywayd you arm ym wgnzmve Personalized hypermedia presentation techniques for improving online customer relationships Alfred Kobsa Jurgen Koenemann Wolfgang Pohl Presented by Satyajit Das Pornpat Nikamanon INF 231 HumanComputer Interaction November 29 2007 Outline Introduction Input data and acquisition methods a User data 3 Usage data c Environment data Representation and secondary inferences Adaptation production Conclusions and prospects INF 231 HumanComputer interaction 275 I Introduction Ecommerce Customer Relationship Software Hypermedia Personalisation techniques INF 231 HumanComputer interaction 375 Ecommerce Scenario in today39s competitive business environment Presales phase Corporate Identity draw attention to products amp senices Sales phase Online storefronts orderingpurchasing facilities Postsales phase 39 Reassurance product support loyalty program INF 231 HumanComputer interaction 475 Costumer Relationship Software Facilitates collection of information about large number of customers interests purchase behavior support needs Dynamic nature updates of contents amp presentation to react to new opportunities amp challenges Global aroundtheclock presence independent of its locality Dynamic creation of content amp presentation for personalised information delivery INF 231 HumanComputer interaction 575 Popular ecommerce website offer personalisation M WaMu mm l i mmquot i mm A DurPrndudsfnr Eustamerszrvme VuurAoun g hgzkmg a Savings c chanAs Erede 5 7 in a m um um mung Welcome back Pornpat Enter Vaur passward i lm a I m m Pumps 74 wan aquot M mi 9 Good News Get 50090 AP 7 m 92 a W seamen My and 6 month term Now at WaMu Lat US WW I Break it aff with Vaur stamps Get a fresh start with a Holiday heartn Spend any way they mam WaMu am Pay We 5 WW Mammals an cm INF 231 HumanComputer interaction 675 Popular ecommerce website offer personalisation Henquot Doluvr wanimmii We havanv you Nam 5 never too early to s V and get FREE snugga uar Iiip 3 39 A a quot Poinpal s Amazon cum i uday s Deals ems miin USISE em paids a YourAccnuni l Heip Saudi Amazun cum v om cemiicaiescaids Free Ecams em Guides Gm Organizer Wisan Wedding Registry Baby Regisirv vawap out FAQ F d sumeune 5 wish Lists Keep track of gift ideas glftcentral Ew 39sm i EB ast gift purchases birthdays ganizer The Holiday Toy List Featuran products with Deliveied l0 Their Door Video d emonstralions p 522 um didmng mafia Eustnmer s Holiday s Favorite Category Huliday Stores Get Amazon Prime Hu iddy Favu Get unlimited FREE TwovDay shipping Tun Sellers ln v 522 all Phen 0E len Ir K Drnaments Ch Idrzn s Hi 9 DEV 3 w Eggkfuuks I w sululiun For sending gifts W f to dlfferent lucatlons lhls Hy Relatlnnilllp I holiday season Read mDrE Mum GirlfriendWife Show all 8 INF 231 HumanComputer interaction 775 Popular ecommerce website offer personalisation Web images Vided N Mag Gmeii meiev Ialstalyajigmallcum i Classic Home i Wee Hlslom i My Admin i Sign DU iGoogle 7 Home iji Sazyaiii H Seaie Addakab I G a m I 7 lE Inbox 41 Hide Dievlew Compose Maii Siddhanhsdec piansLAee mai daiirdmia a aiia iiii 2 555am Pumpalrplclure or sea party a l am Pompai 2 7 Chat With Fompal leamancn 7 Hi W am Nov i7 Adobe VVOUFAdObE Membership 7 Thank ydd oi semi Nov 17 Vivek a lnvlla a to View Vivek K s Fmasa Web Album Nov 16 um i 2 e s e 7 I a In ii immsian Eimzmmi zzzam Wlklg did 1 39ii 2 1 1 5 n 7 H wmhar i W In Search A dEvenl 5quot l Irvine CA 5 Today Mon Tue Wed TuDn Lm Haze 39i quot i i Huwm onhe Day gt Wind N ale mph 2 Newllem Add H d sava i i Hmim Re airaaadk s Bindiii l W W W 53 gm 65 53 WW Haw m Bake Bread Ea5kels Ounnmlu m Gungl Logn Tug Starla CNNme Lbs Angeies Times a an 363 related n ma iiv ii Miis I ember kills kids as Us mug hand out toys ham ii end em and rule INF 231 HumanComputer interaction 875 Popular ecommerce website offer personalisation m snanpchana Women Men shy Kins Hume Ee v am mm ur a Sumquot NW7de 3 r Aiichznrvc is invmgmzm in Target Weekly Ad W 3quot vie Go Paperless39 WW i 4 mm i 1m CIICk and Save A min squot View i i Target Calalogs i i l 7 1 men a INF 231 Human Computer interaction 975 Personalised Hypermedia Application A system which adapts the content structure andor presentation of the networked hypermedia objects to each individual users characteristics usage behavior and usage environment There are different basic types of adaptation depending upon the amount of control user has over the adaptation 39 Adaptive system system performs all steps autonomously 71 User controlled adaptivity the system lets the user make selection and performs the adaptation 391 User initiated adaptivity user request and lets the system decide the best option INF 231 Human Computer interaction 1075 lPersonalised Hypermedia Application Adaptive system n AVANTI Tourist information system This is a result of Adaptivity which means that the system recognizes that the user is interested in churches thus it highlights the corresponding options INF 231 HumanComputer interaction 1175 Input data and acquisition methods Different types of the data and methods of acquiring the information about the user39s characteristics computer usage behavior and usage environment which are required in adapting the system to the user39s needs User data 393 Usage data a 139 Environment data INF 231 HumanComputer interaction 1275 Input data and acquisition methods User data ir Personal characteristics of the user 1 Demographic data m User knowledge m User skills and capability m User interests and preferences m User goals and plans INF 231 HumanComputer interaction 1375 User data Demographic data 7 Wm WWIquot 7 J INF 231 HumanComputer interaction 1475 User data User Knowledge data Assumptions about users39 knowledge about concepts relationships between concepts and facts and rules with regard to the domain of the 39 39 are L 39 for 39 39 Examples Restricting or increasing the explanatory pages to be presented to the user depending on his or her expertise Generating expertise dependent product description Intelligent tutoring systems WP 231 e Humanrcomputer interaction 1575 Conditional text Presentation Concept c being presented Tne presentation rne Wgsemamn The presentation oiooneeptt 7 mm c L ufcnncepic tar an expert user tor an Wigwam rare novice user user WP 231 Humanrcomputer interaction 1575 Conditional text Presentation ILEX adaptive learning system Generates interesttailored descriptions of objects which are tuned to different user interests INF 231 HumanComputer interaction 1775 User data User Skills and capabilities Knowledge of the ability and skills of the users plays an important role in adapting systems to users needs The system may also distinguish between the actions a user is familiar with and the actions he or she is actually able to perform It is possible that a user knows how to do something but is not able to perform the action due to lack of required permissions or to some physical handicap Example 1 Adaptive help systems INF 231 HumanComputer interaction 1875 User data Tourist information system AVANTI takes the needs of different kinds of disabled people wheelchairbound motorimpaired amp visionimpaired into account therefore only recommends actions that these users are actually able to perform INF 231 Human Computer interaction 1975 User data User interests and preferences Interests among users of the same application often vary considerably Example Promotion of cars to different audiences conflicting sets of attributes speed sexappeal safety family friendliness must be emphasised INF 231 Human Computer interaction 2075 1O User data User interests and preferences User interest is a central notion for the Recommendation systems The items recommended may be products services documents news and so on VB m 3 mm an HIV y m xquot iNF 2317 Humaanomputer interaction 2175 User data User interests and preferences 4 with Wnich they are already familiar Wmm mmmumt mm m M i iNF 2317 Humaanomputer interaction 2275 iUser data User goals and plans Typical goals may be to find information on a certain topic or to shop for some kind of product A system that supports users in achieving their goals facilitates and speeds up interaction considerably since the system has expectations about the next user actions and can therefore interpret them in a more flexible way INF 231 HumanComputer interaction 2375 i User data User goals and plans User Assistam agem PlanRecognition Mi edim ia w mwmcuon Observesand imi es Acts in userbehalf i L 7 39 Application 2 Aims at identifying the goal or intention of the user based on the actions they perform in an environment Narrows the number of possible goals by observing the actions the user performs INF 231 HumanComputer interaction 2475 User data User goals and plans Plan Recog1ition Inputs and outputs Inputs 2 a setof goals the user carries out in the domain a setof plans describing the way in which the user can reach each oal i an useraction observed by the system Output foretelling me user39s goal and determining how me observed action contributes to reach it INF 231 7 Hu mann omputer interaction 2575 User model acquisition methods User supplied info rmation Active acquisition U er data is acquired through questions asked by me system typically in an initial phase of system usage 7 u Caution Selfassessment is errorprone since users are often not correc y aware of things like meir own capabilities Some systems therefore present controlled queries tests exercises that are aimed at a more objective assessment of the user INF 231 7 Hu mannComputer interaction User model acquisition methods User supplied information Downside of active acquisition Paradox of the Active User Users are motivated to get started and are in a hurw to get their immediate task done In cases of competing information sources users may simply refuse to visit the site if they have to respond to an intewiew first The paradox is information acquired will be helpful in adapting the system and making in more userfriendly in the long run The acquisition phase should therefore be minimised and ideally be administered only after the user has already obtained some impression about the benefits the site has to offer INF 231 HumanComputer interaction 2775 User model acquisition methods Stereotype reasoning A simple method for making a first assessment of others is to classify them into categories and to then make predictions about them based on a stereotype that is associated with each category Main components of stereotype are 39 a body which contains information that is typically true of users to whom the stereotype applies a set of activation conditions triggers for applying the stereotype to a user Wm mi Use 53 um modal shows lhal he use Pamm is inleresle in mudme usaga Dam niar bungquot two has armysum 39F arent39 Usage Environmgm lhheusersbrowserlsa recent Compu emiwd beta version INF 231 HumanComputer interaction 2875 Usage data Observable usage a Selective actions Temporal viewing behavior 5 Ratings Purchases and purchaserelated actions Other confirmatory and disconfirmatory actions Usage regularities INF 231 HumanComputer interaction 2975 Usage data Observable usage Selective actions User makes a choice if competitive W 7 7 7 links are available on the current page m w HT f fj n quoti ii 7 Huwiu Make a Lhiislmas True F mo Lil tam Actions iGoogle f Clicking link Scrolling and enlarging operation pe misss Document expanSion operation E Mm it if Movie and audio operation 7 2 Other actions at user interfaces 1 m W m campadiciassicinil u Interest 57 FF Unfamiliarity 1 Preferences mm My Mum Mew iivinei CA 59 ISD39 55 Ma39 57 m MY YAHOO INF 231 HumanComputer interaction 3075 Usage data Obsewable usage Temporal viewing behavior Viewing time Difficulty of measurement I 2 User not present in front of the computer i39 Window is covered by other windows Item is outside the visible window area Negative evidence not interesting to user r Presentation time less than certain threshold Abort download Presses the back button shortly after the page download commenced Rihanna Umbrella ii share a watch again Streamed data videoaudio 39 User reaction shortly after termination i User interest in this streaming BE FLASH w 39 39 14v I Further research t Micro interaction level 7 a Usage of eyetracking YouTube INF 231 Human Computer interaction 3175 Usage data Obsewable usage Ratings Users are required to explicitly rate objects Al Your SlUC I 2 How relevantinteresting to user bv the u Euc c How relevantInteresting to other user Rating type 39 Binary scale I donquott like if I like if 7 Numeric scale H I hate it I donquott like if It39s OK I like if I love if Gm 7 35quot Pandora Problem Relevance is always relative changing User not rate Interaction Design by Jenny Preece I love it Amazencem purchase xi Yourta 5 This was a gift 9 s L l ms Whatls thig L Ee jcgls39lESnfc ljartipns Clicklno Add g interaction design internet interface design user interface school wish list Amazon INF 231 Human Computer interaction 3275 16 Usage data Observable usage Purchases and purchaserelated actions INF 231 HumanComputer interaction A purchase is a strong indicator of user interest in some of the features of the purchased product React adaptively by suggesting similar or related items No onetoone mapping between purchases and interests Purchase for other people gift Already own on available item meessinnal Model Portfolios A Ste gibyisteg Guide for thtugraghers by Billy Pegram Aug 23 2mm umer Review W 7 5 In Stock List Price 3435 Fri 42307 IWI Add mWISh List 1 42 used a new frum 21 24 um it Noumea unseen e he it R Dmmende Amazon INF 231 HumanComputer interaction 3375 Other confirmatory and disconfirmatory actions Strengthen an assumption in concert with a preceding selection Examples quot quot Vquotl Saving n a m Irena Printing We I Bookmarking Mm Huqu mm 76 used Elt new Forwarding by email 2 F39 Have one m 52H7 l Snllyumshnml l I Add aim in s i W quotquot quotW Overview Thisi e rirg39mf u FDSSEZSEWES i Addm ahykegistry j andusavs The ir W was Reglsualmn is mi 333 W7 Emma navel mierface m re acls an paianl gt 7 Hevsnnallzaiwn Amazon ZDNet 3475 Usage data Usage regularities Further processing of usage data to acquire information about users preferences habits and levels of expertise User frequency i Categorize events and count theirfrequencies Egtltamples Microsoft word Adaptive icon toolbar AVANTI Introduce shortcut links Situationaction correlations Interface agents personal assistants Suggestions based on statistics correlations between previous situations and action Action sequences Recommend the generation of macros Predict future user actions Recommend actions INF 231 HumanComputer interaction rm Vu ilcmzziaii ii m ems 0726 WWW 000206 3575 Environment data Constraints Software environment Hardware environment Locale Mapping model Singleuser machine Multiuser machine INF 231 HumanComputer interaction 3675 Environment data Software environment Browser version and platform Availability of plugins e Java and JavaScript 0 39 UserAgent Mozilla40 compatible MSIE 60 Windows NT 51 8V1 Header of HTTP requests INF 231 HumanComputer interaction 3775 hm lwwwehayunivrsilycnm r anilla Filelnx Sofl 4 m me i i B Click the button below m upgrade esh m the most current VErSiDH Hea Dane INF 231 HomanComputer interaction 3875 Environment data Hardware environment Bandwidth Processing speed Display devices i Input devices INF 231 Human Computer interaction 3975 Environment data Locale Users current location Characteristics of usage locale noise level brightness of the surrounding etc INF 231 Human Computer interaction 4075 20 Representation and secondary inferences Most common representation approaches and the inference techniques Deductive reasoning from the more general to the more specific Logicbased representation and inference Representation and reasoning with uncertainty Inductive reasoning from specific cases to the general case Learning about the user Analogical reasoning from similar cases to the present case Cliquebased filtering Clustering user profiles A hybrid approach user profiles as learning results INF 231 HumanComputer interaction 4175 IV Adaptation production Adaptation Production explains the possible types of adaptation to the user usage and environment data of an individual user Adaptations in hypermedia systems can take place at different levels that we will discuss in the following sections Adaptation of content Adaptation of presentation and modality Adaptation of structure INF 231 HumanComputer interaction 4275 21 content of hypermedia objects and pages in accordance with user usage and environment data m Personalization functions of content adaptation e Techniques for content adaptation INF 231 HumanComputer interaction Adaptation of content Adaptation of Content describes methods for personalising the 4375 Adaptation of content Personalisation functions Personalise n ons ation Optional explanations help users who lack the necessary background knowledge better understand Optional detailed information can improve the relevance of a hypermedia page for users who are interested Personalized recommendations inform users about available offerings in which they may be interested adaptive comparison that relates new information a user quotvivchch w 39 are based on users39 presumed interesls and on E9 news ashes INF 231 HumanComputer interaction 4475 22 Adaptation of content Techniques Techniques for content adaptation A number of techniques on different levels of granularity and localisation have been developed so far for adapting hypermedia content to different user needs i Page variants quot Fragment variants Fragment coloring Adaptive stretchtext Adaptive naturallanguage generation INF 231 HumanComputer interaction 4575 Adaptation of content Techniques Page variants Authoring different versions of all pages in which adaptation occurs Adaptation at runtime is confined to adaptive page selection Cumbersome since a completely new page has to be written for each variation of local adaptations that may occur on a page nflegtltible since many pages have to be modified if a single local adaptation is changed INF 231 HumanComputer interaction i select a Theme For Tlus nu L quot ll Classlc E mquot 57 m A m u m m mm mm W M m m lt l iGoogle 23 Adaptation of content Techniques Fragrant variants M quotwwwzm 72 MusllvcluuW Tuna Dquot THE Wind Salizmph H may 9 a 7 mm mMa 69w Authored for each adaptive page fragment sum Valley CA WWW MDquot 391 At runtime the appropriate fragments are g 3 included into a static page frame It requires the dynamic generation of web pages at runtime The granularity of a page fragment iGoo le A paragraph of text g An image 39 i A table Apaga ufinformalionto be presented A Video PagefragmenlA Fragment A has EI39IBD Page fragmenlB Fragment E has 2 variants Page fragment 0 gt lt39 Fragment C has rianls INF 231 Human Computer interaction 4775 Adaptation of content Techniques Fragrant colouring The content of the hypermedia remains unchanged across all users For each individual user g i llcsnmm rg of the hypermedia presentation are marked out eg as being important irrelevant or too demanding for him or her Fragment colouring can only be applied in such areas where content can be presented in the same formulation to all users and where the variability of adaptation across all users is relatively low INF 231 Human Computer interaction 4875 24 Adaptation of content Techniques Adaptive Stretchtext Stretchtext is elastic text that the user can extend or collapse by clicking on it with the mouse Stretchtext can be automatically expanded and collapsed by the system taking the user model into account Users can adapt the page content manually if the adaptation that was automatically performed by the system is not appropriate or desired INF 231 Human Computer interaction 4975 Adaptation of content Techniques Correct spelling and grammar Word provides two ways lo th spelling and grammar As you type Word can automatically check your document and underline possible spelling and grammatical errors To colmm an error display a 5 0mm menu and r uckzmzhulc r 1 2 Enlmcklun dz WA ule A menu lhal shows a list 0 commands mm m a particular item m lairhum neraounummy darnlulu um nilinllch my vanmm dn Atm39notgln mm mm m um all mamu x u n u Wo d lulvasthln inch um Iymhnliuhln Sum nmmln m hm Faun Irmmlsulu hwn u l m mmm harm MAB das mum Mansdl amen mam g In due MIquot M Mlbnlsiula mum amen much a mum mmanon ordlm m 9mm in mm Im minkei gumalumna lammm mum m ln we Lagn an magnum bum an m an em mm ay physhlng schu Kmmmung deIWirbelsamo mm min um Sn 12 mum Belushimg amermhm Munich may a pal mm Edenn Fallisi em em in 2 elem thelsiulembleme Ah My wucklung In sum on Tachmsunmg and an mus rmhllunden mudmn Erllicmumlgin mammal musn numb ea Mme mammal gure 7 KNVAIE adapuvc hypermedlu course Ruckznschulequot INF 231 Human Computer interaction 5075 25 Adaptation of content Techniques Adaptive naturallanguage generation Natural language generation techniques to create alternative text descriptions for different users A simple approach are text templates with slots that can be filled with descriptions of different complexity based on the user s level of expertise Naturallanguage generation also seems to be a promising complement to stretchtext INF 231 HumanComputer interaction 5175 Adaptation of content Techniques l czlrlschuins M Ami Wire Earrings Figure 9 39 39 Fig 3 Generates interesttailored descriptions of objects which are tuned to different user interests INF 231 HumanComputer interaction 5275 26 Adaptation of presentation and modality Adaptations of presentation are adaptations where the information content of the hypermedia objects ideally stays the same while the format and layout of the objects change Change of modality images to text from text to audio or from video to still images Adaptation in hypermedia systems concerning multimedia presentations are often based on User s preferences User s physical abilities System performance INF 231 HumanComputer interaction 5375 Adaptation of presentation and modality y z A Figure In AVAICH Sim my m graphical mm gure 11 AVANTI Siam mp for blind people lvlsuzil Epmscmanon of auditory output Modality image has been changed to text based on the selection of different modalities by the user s physical abilities INF 231 HumanComputer interaction 5475 27 Adaptation of presentation and modality Adapted document Adapted docu ment39 Adapted documentH Ada ptation INF 231 HumanComputer interaction 5575 Adaptation of structure Adaptation of structure refers to changes in the way in which the link structure of hypermedia documents or its presentation to users is changed Techniques for structure adaptation Adaptive link sorting Adaptive link annotation Adaptive link hiding and unhiding Adaptive link disabling and enabling Adaptive link removal addition INF 231 HumanComputer interaction 5675 28 Adaptation of structure Techniques Adaptive link sorting Primarily employed for ranking the target web pages based on their relevance to users interests and goals and their appropriateness for the user based on the user s background knowledge example ranked lists of recommended items such as movies ranked lists of recommended items as technical equipment frequency of use eg in personalised views and spaces The sorting of link lists can be used for noncontextual links only Downside Caution should be exercised however since automatic item sorting in menus based on usage frequency has been found to potentially confuse users INF 231 HumanComputer interaction 5775 Adaptation of structure Techniques Adaptive link annotation Links that have already been visited change their colours This is non adaptive link annotation is well known from all major web browsers There are up to six different annotations with the following meanings suggested ready inferred known done and notready Adaptive hypermedia systems use different colours and symbol codes to annotate links in a personalised manner INF 231 HumanComputer interaction 5875 Adaptation of structure Techniques Adaptive link hidingunhiding Adaptive link hiding removes the visible cue of a link in such a way that the link anchor looks like normal text or a normal icon The idea is to visually reduce the hyperspace to support users navigation and to guide users to those pages which the system assumes to be the currently most relevant ones or that are probably comprehensible to the user given his or her presumed level of knowledge INF 231 HumanComputer interaction 5975 Adaptation of structure Techniques Adaptive link disabling and enabling Link disabling removes the functionality of a link but leaves its visual appearance nearly untouched ie the link anchor still looks like a link but nothing happens when one clicks on it Disabled Link Downside This behaviour of a link considerably violates the principle of expectation conformance in humancomputer interaction link disabling and enabling is currently used together with link hiding and unhiding only INF 231 HumanComputer interaction 6075 30 Adaptation of structure Techniques Adaptive link removaladdition Adaptive link removal deletes the link anchors completely Its is an effective way to support users navigation by reducing the number of navigation steps to achieve a certain goal and by reducing the user s cognitive overload This technique can only be applied to noncontextual links example removal of links to pages which are not yet appropriate for a learner removing links to irrelevant subtasks removing items in a product listing that are probably of no interest to the user Downsidez if a stable listing of links is used frequently removal of individual links would also violate the constancy principle of human computer interaction and should therefore be used with caution INF 231 HumanComputer interaction 6175 Adaptation of structure Techniques F59 De 44 1w 6 ownmew an 39 Back a Home Scmch Glade Pm Sonny J saomak A Lowan I39p r r mmquot 1 sqmumzt mmw J Figure 12 RecommendmmnofnezubypaintingsmHLVS HIPS Mobile webbasedMuseum guide Link addition system automatically introduces links to nearby paintings and also links to more distant paintings based on user interest in their topic painter and time periods of paintings that the user visited before INF 231 HumanComputer interaction 6275 31 Adaptation of structure Personalisation functions Some personalisation functions of structure adaptation Adaptive recommendations Adaptive orientation and guidance Personal views and spaces INF 231 HumanComputer interaction 6375 Adaptation of structure Personalisation functions Adaptive recommendations Recommendations concerning products Lists of links to products and senices are filtered or ranked based on user data and presented to the user Amazoncom moviefindercom Recommendation concerning information Lists of links to documents or other pieces of information are ranked based on user and usage data Recommended news Google news Navigation recommendations Links to hypermedia pages usually at the same site are filtered or ranked based on user usage and environment data Systems customised for different user profiles INF 231 HumanComputer interaction 6475 32 Adaptation of structure Personalisation functions Adaptive orientation and guidance Overview maps Personalised overview maps mark those pages that users visited or bookmarked in the past Guided site tours Personalised guided tours can take user data into account and modify the tour so that it caters better to users presumable interests It helps in familiarising firsttime users with the basic offerings of a website Personalised next buttons This is a very flexible method for the presentation of learning material because the destination node of the next button is not directly connected to the current node but can be dynamically computed at runtime taking even the very last actions of the user into account INF 231 HumanComputer interaction 6575 Adaptation of structure Personalisation functions Personalised view bookmarking facilities that are integrated into most current web browsers provide users with personalised access to web resources generate shortcuts for frequently followed links 6 Firefox File am View Hismry Ewkmirks Tnais Wlndcw Help deliious 0003 BookmarkThisPage 3gp b Bookmark AllTabs Ich WWW m umu s Omnmmkm m dellcmlus a mm quot ms 0 K55 a Q j V Toolbar Favorites y TalkCadget the information Age all your bookmarks in one place California ins ormatlon Technology Newzl mm m uuwammwm Mammals check out what other people are bookmarking QAVANTl mu K ishnaEajracharyahddywikki 9 My TiddlyWiki 7 my page INF 231 HumanComputer interaction 6675 Adaptation of structure Personalisation functions Personalised Space I view histories of their past actions eg purchases and reservations I set markers eg for books to buy in the future define shortcuts to sitespecific resources they frequently access I specify information they want to have forwarded to them automatically eg quotes for certain stocks news from certain categories i save documents and news in a personal repository INF 231 Human Computer interaction 6775 Adaptation of structure Personalisation functions Web Images vim Nws Mag Gmail mmev Personalised Space 00816 NNNNN nm iGoogle 5mm zils lt casmws i y SlapimnallPieaseselmyoulLmailpmd Yupmdw Hunk snimnmmm Mm Fleahmk u mm Milly um aan w wnn m pnapln Iround m mogm facebook 3 mamWWW mumWm u 11mm naman yet wu n Egismr mw Netvibes INF 231 Human Computer interaction 6875 34


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