A System for Context-Dependent User Modeling
Identifieur interne : 000957 ( Main/Exploration ); précédent : 000956; suivant : 000958A System for Context-Dependent User Modeling
Auteurs : Petteri Nurmi [Finlande] ; Alfons Salden [Pays-Bas] ; Sian Lun Lau [Allemagne] ; Jukka Suomela [Finlande] ; Michael Sutterer [Allemagne] ; Jean Millerat [France] ; Miquel Martin [Allemagne] ; Eemil Lagerspetz [Finlande] ; Remco Poortinga [Pays-Bas]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2006.
English descriptors
- Teeft :
- Algorithm, Behavior information, Best knowledge, Carnegie mellon university, Component diagram, Context information, Context management framework, Context parameters, Context providers, Current implementation, Current situation, Design goals, Design process, Diverse domains, Entire system, External components, Future work, Good mapping, Group members people, International conference, Mapper, Mobile applications, Mobile device, Mobile systems, Modality recommendations, Modeling, Neural networks, Output modality, Personal communicator, Predictive user models, Proc, Project mobilife, Provider, Reasoner, Recommender, Rule induction, Service categories, Service category recommendations journey planners, Speech output, Usage information, Usage record, Usage record provider, Usage records, User, User modeling, User modeling algorithms, User modeling system, User models.
Abstract
Abstract: We present a system for learning and utilizing context-dependent user models. The user models attempt to capture the interests of a user and link the interests to the situation of the user. The models are used for making recommendations to applications and services on what might interest the user in her current situation. In the design process we have analyzed several mock-ups of new mobile, context-aware services and applications. The mock-ups spanned rather diverse domains, which helped us to ensure that the system is applicable to a wide range of tasks, such as modality recommendations (e.g., switching to speech output when driving a car), service category recommendations (e.g., journey planners at a bus stop), and recommendations of group members (e.g., people with whom to share a car). The structure of the presented system is highly modular. First of all, this ensures that the algorithms that are used to build the user models can be easily replaced. Secondly, the modularity makes it easier to evaluate how well different algorithms perform in different domains. The current implementation of the system supports rule based reasoning and tree augmented naïve Bayesian classifiers (TAN). The system consists of three components, each of which has been implemented as a web service. The entire system has been deployed and is in use in the EU IST project MobiLife. In this paper, we detail the components that are part of the system and introduce the interactions between the components. In addition, we briefly discuss the quality of the recommendations that our system produces.
Url:
DOI: 10.1007/11915072_97
Affiliations:
- Allemagne, Finlande, France, Pays-Bas
- Bade-Wurtemberg, District de Karlsruhe, District de Kassel, Hesse (Land), Uusimaa, Île-de-France
- Cassel (Hesse), Gif-sur-Yvette, Heidelberg, Helsinki
- Université d'Helsinki
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Le document en format XML
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Box 68, FI-00014</wicri:regionArea><orgName type="university">Université d'Helsinki</orgName><placeName><settlement type="city">Helsinki</settlement><region type="région" nuts="2">Uusimaa</region></placeName></affiliation><affiliation wicri:level="1"><country wicri:rule="url">Finlande</country></affiliation></author><author><name sortKey="Poortinga, Remco" sort="Poortinga, Remco" uniqKey="Poortinga R" first="Remco" last="Poortinga">Remco Poortinga</name><affiliation wicri:level="1"><country xml:lang="fr">Pays-Bas</country><wicri:regionArea>Telematica Instituut (TELIN), P.O. Box 589, 7500, Enschede, AN</wicri:regionArea><wicri:noRegion>AN</wicri:noRegion></affiliation><affiliation wicri:level="1"><country wicri:rule="url">Pays-Bas</country></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2006</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="Teeft" xml:lang="en"><term>Algorithm</term><term>Behavior information</term><term>Best knowledge</term><term>Carnegie mellon university</term><term>Component diagram</term><term>Context information</term><term>Context management framework</term><term>Context parameters</term><term>Context providers</term><term>Current implementation</term><term>Current situation</term><term>Design goals</term><term>Design process</term><term>Diverse domains</term><term>Entire system</term><term>External components</term><term>Future work</term><term>Good mapping</term><term>Group members people</term><term>International conference</term><term>Mapper</term><term>Mobile applications</term><term>Mobile device</term><term>Mobile systems</term><term>Modality recommendations</term><term>Modeling</term><term>Neural networks</term><term>Output modality</term><term>Personal communicator</term><term>Predictive user models</term><term>Proc</term><term>Project mobilife</term><term>Provider</term><term>Reasoner</term><term>Recommender</term><term>Rule induction</term><term>Service categories</term><term>Service category recommendations journey planners</term><term>Speech output</term><term>Usage information</term><term>Usage record</term><term>Usage record provider</term><term>Usage records</term><term>User</term><term>User modeling</term><term>User modeling algorithms</term><term>User modeling system</term><term>User models</term></keywords></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: We present a system for learning and utilizing context-dependent user models. The user models attempt to capture the interests of a user and link the interests to the situation of the user. The models are used for making recommendations to applications and services on what might interest the user in her current situation. In the design process we have analyzed several mock-ups of new mobile, context-aware services and applications. The mock-ups spanned rather diverse domains, which helped us to ensure that the system is applicable to a wide range of tasks, such as modality recommendations (e.g., switching to speech output when driving a car), service category recommendations (e.g., journey planners at a bus stop), and recommendations of group members (e.g., people with whom to share a car). The structure of the presented system is highly modular. First of all, this ensures that the algorithms that are used to build the user models can be easily replaced. Secondly, the modularity makes it easier to evaluate how well different algorithms perform in different domains. The current implementation of the system supports rule based reasoning and tree augmented naïve Bayesian classifiers (TAN). The system consists of three components, each of which has been implemented as a web service. The entire system has been deployed and is in use in the EU IST project MobiLife. In this paper, we detail the components that are part of the system and introduce the interactions between the components. In addition, we briefly discuss the quality of the recommendations that our system produces.</div></front></TEI><affiliations><list><country><li>Allemagne</li><li>Finlande</li><li>France</li><li>Pays-Bas</li></country><region><li>Bade-Wurtemberg</li><li>District de Karlsruhe</li><li>District de Kassel</li><li>Hesse (Land)</li><li>Uusimaa</li><li>Île-de-France</li></region><settlement><li>Cassel (Hesse)</li><li>Gif-sur-Yvette</li><li>Heidelberg</li><li>Helsinki</li></settlement><orgName><li>Université d'Helsinki</li></orgName></list><tree><country name="Finlande"><region name="Uusimaa"><name sortKey="Nurmi, Petteri" sort="Nurmi, Petteri" uniqKey="Nurmi P" first="Petteri" last="Nurmi">Petteri Nurmi</name></region><name sortKey="Lagerspetz, Eemil" sort="Lagerspetz, Eemil" uniqKey="Lagerspetz E" first="Eemil" last="Lagerspetz">Eemil Lagerspetz</name><name sortKey="Lagerspetz, Eemil" sort="Lagerspetz, Eemil" uniqKey="Lagerspetz E" first="Eemil" last="Lagerspetz">Eemil Lagerspetz</name><name sortKey="Nurmi, Petteri" sort="Nurmi, Petteri" uniqKey="Nurmi P" first="Petteri" last="Nurmi">Petteri Nurmi</name><name sortKey="Suomela, Jukka" sort="Suomela, Jukka" uniqKey="Suomela J" first="Jukka" last="Suomela">Jukka Suomela</name><name sortKey="Suomela, Jukka" sort="Suomela, Jukka" uniqKey="Suomela J" first="Jukka" last="Suomela">Jukka Suomela</name></country><country name="Pays-Bas"><noRegion><name sortKey="Salden, Alfons" sort="Salden, Alfons" uniqKey="Salden A" first="Alfons" last="Salden">Alfons Salden</name></noRegion><name sortKey="Poortinga, Remco" sort="Poortinga, Remco" uniqKey="Poortinga R" first="Remco" last="Poortinga">Remco Poortinga</name><name sortKey="Poortinga, Remco" sort="Poortinga, Remco" uniqKey="Poortinga R" first="Remco" last="Poortinga">Remco Poortinga</name><name sortKey="Salden, Alfons" sort="Salden, Alfons" uniqKey="Salden A" first="Alfons" last="Salden">Alfons Salden</name></country><country name="Allemagne"><region name="Hesse (Land)"><name sortKey="Lau, Sian Lun" sort="Lau, Sian Lun" uniqKey="Lau S" first="Sian Lun" last="Lau">Sian Lun Lau</name></region><name sortKey="Lau, Sian Lun" sort="Lau, Sian Lun" uniqKey="Lau S" first="Sian Lun" last="Lau">Sian Lun Lau</name><name sortKey="Martin, Miquel" sort="Martin, Miquel" uniqKey="Martin M" first="Miquel" last="Martin">Miquel Martin</name><name sortKey="Martin, Miquel" sort="Martin, Miquel" uniqKey="Martin M" first="Miquel" last="Martin">Miquel Martin</name><name sortKey="Sutterer, Michael" sort="Sutterer, Michael" uniqKey="Sutterer M" first="Michael" last="Sutterer">Michael Sutterer</name><name sortKey="Sutterer, Michael" sort="Sutterer, Michael" uniqKey="Sutterer M" first="Michael" last="Sutterer">Michael Sutterer</name></country><country name="France"><region name="Île-de-France"><name sortKey="Millerat, Jean" sort="Millerat, Jean" uniqKey="Millerat J" first="Jean" last="Millerat">Jean Millerat</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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