On Embedding Task Memory in Services Composition Frameworks
Identifieur interne : 000485 ( Istex/Curation ); précédent : 000484; suivant : 000486On Embedding Task Memory in Services Composition Frameworks
Auteurs : Rosanna Bova [France] ; Hye-Young Paik [Australie] ; Salima Hassas [France] ; Salima Benbernou [France] ; Boualem Benatallah [Australie]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2007.
Descripteurs français
- Wicri :
- topic : Conférence internationale, Ontologie.
English descriptors
- KwdEn :
- Actual service, Adviser agent, Attribute, Avgs, Bova, Bpel, Bpel skeleton, Builder agent, Business travel task, Computer science, Context, Context agent, Context attributes, Context awareness, Context classes, Context information, Context ontology, Context query summary, Context summary, Context summary queries, Context summary query, Dynamic environments, Editing process, Elementary task, Embedding, Embedding task memory, Event monitoring service, Event patterns, Flight reservation, General area, Georgia institute, Global affinity, Hong kong, Incremental acquisition techniques, Infrastructure services layer, International conference, Invocation, Large databases, Large number, Ontology, Other approaches, Other words, Parallel databases, Past experience, Personal information management, Planning task, Possible combinations, Query, Rank services, Relevant candidate, Relevant candidate services, Relevant contexts, Rental service, Routine tasks, Selection approaches, Selection component, Service attributes, Service capabilities, Service categories, Service combinations, Service composition, Service discovery engine, Service infrastructure, Service ontologies, Service ontology, Service operation, Service properties, Service schema, Service selection, Service selection events, Service selection techniques, Service usage history, Service usage patterns, Services combination, Services composition, Services composition frameworks, Services discovery, Services ontologies, Services selection, Similar contexts, Similar services, Specific task, State chart, State charts, Summary attributes, System administrator, Task definition, Task memories, Task memory, Task memory builder agent, Task memory table, Travel booking task, Travel planner, University lyon, Usage table, User, User agent, User query, User task.
- Teeft :
- Actual service, Adviser agent, Attribute, Avgs, Bova, Bpel, Bpel skeleton, Builder agent, Business travel task, Computer science, Context, Context agent, Context attributes, Context awareness, Context classes, Context information, Context ontology, Context query summary, Context summary, Context summary queries, Context summary query, Dynamic environments, Editing process, Elementary task, Embedding, Embedding task memory, Event monitoring service, Event patterns, Flight reservation, General area, Georgia institute, Global affinity, Hong kong, Incremental acquisition techniques, Infrastructure services layer, International conference, Invocation, Large databases, Large number, Ontology, Other approaches, Other words, Parallel databases, Past experience, Personal information management, Planning task, Possible combinations, Query, Rank services, Relevant candidate, Relevant candidate services, Relevant contexts, Rental service, Routine tasks, Selection approaches, Selection component, Service attributes, Service capabilities, Service categories, Service combinations, Service composition, Service discovery engine, Service infrastructure, Service ontologies, Service ontology, Service operation, Service properties, Service schema, Service selection, Service selection events, Service selection techniques, Service usage history, Service usage patterns, Services combination, Services composition, Services composition frameworks, Services discovery, Services ontologies, Services selection, Similar contexts, Similar services, Specific task, State chart, State charts, Summary attributes, System administrator, Task definition, Task memories, Task memory, Task memory builder agent, Task memory table, Travel booking task, Travel planner, University lyon, Usage table, User, User agent, User query, User task.
Abstract
Abstract: With the increasing availability of Web services and adoption of services oriented paradigm, there is a growing need to dynamically compose services for realizing complex user tasks. While service composition is itself an important problem, a key issue is also how to support users in selecting the most appropriate compositions of services to fulfill a task. In existing dynamic services selection approaches, combinations of services are repeatedly discovered (e.g., using ontology-based matching techniques) and selected by users whenever needed. To improve their effectiveness, we propose a new technique that provides an efficient access to what is named a “task memory”. A task memory is used to provide users with a context-aware service selection by recommending combinations of services that are most appropriate in a given context. A task memory is formed using the service composition history and their metadata. We present an incremental approach for building the task memory in which we monitor how users use and rank the services. The continuous updates of the task memory over time will result in more fine-tuned recommendations for composite services.
Url:
DOI: 10.1007/978-3-540-73597-7_1
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hassas@bat710.univ-lyon1.fr</mods:affiliation><country wicri:rule="url">France</country></affiliation></author><author><name sortKey="Benbernou, Salima" sort="Benbernou, Salima" uniqKey="Benbernou S" first="Salima" last="Benbernou">Salima Benbernou</name><affiliation wicri:level="1"><mods:affiliation>LIRIS, University Lyon 1, France</mods:affiliation><country xml:lang="fr">France</country><wicri:regionArea>LIRIS, University Lyon 1</wicri:regionArea></affiliation><affiliation wicri:level="1"><mods:affiliation>E-mail: salima.benbernou@liris.cnrs.fr</mods:affiliation><country wicri:rule="url">France</country></affiliation></author><author><name sortKey="Benatallah, Boualem" sort="Benatallah, Boualem" uniqKey="Benatallah B" first="Boualem" last="Benatallah">Boualem Benatallah</name><affiliation wicri:level="1"><mods:affiliation>CSE, University of New South Wales, Australia</mods:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>CSE, University of New South 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information</term><term>Context ontology</term><term>Context query summary</term><term>Context summary</term><term>Context summary queries</term><term>Context summary query</term><term>Dynamic environments</term><term>Editing process</term><term>Elementary task</term><term>Embedding</term><term>Embedding task memory</term><term>Event monitoring service</term><term>Event patterns</term><term>Flight reservation</term><term>General area</term><term>Georgia institute</term><term>Global affinity</term><term>Hong kong</term><term>Incremental acquisition techniques</term><term>Infrastructure services layer</term><term>International conference</term><term>Invocation</term><term>Large databases</term><term>Large number</term><term>Ontology</term><term>Other approaches</term><term>Other words</term><term>Parallel databases</term><term>Past experience</term><term>Personal information management</term><term>Planning task</term><term>Possible combinations</term><term>Query</term><term>Rank 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selection</term><term>Similar contexts</term><term>Similar services</term><term>Specific task</term><term>State chart</term><term>State charts</term><term>Summary attributes</term><term>System administrator</term><term>Task definition</term><term>Task memories</term><term>Task memory</term><term>Task memory builder agent</term><term>Task memory table</term><term>Travel booking task</term><term>Travel planner</term><term>University lyon</term><term>Usage table</term><term>User</term><term>User agent</term><term>User query</term><term>User task</term></keywords><keywords scheme="Teeft" xml:lang="en"><term>Actual service</term><term>Adviser agent</term><term>Attribute</term><term>Avgs</term><term>Bova</term><term>Bpel</term><term>Bpel skeleton</term><term>Builder agent</term><term>Business travel task</term><term>Computer science</term><term>Context</term><term>Context agent</term><term>Context attributes</term><term>Context awareness</term><term>Context classes</term><term>Context information</term><term>Context ontology</term><term>Context query summary</term><term>Context summary</term><term>Context summary queries</term><term>Context summary query</term><term>Dynamic environments</term><term>Editing process</term><term>Elementary task</term><term>Embedding</term><term>Embedding task memory</term><term>Event monitoring service</term><term>Event patterns</term><term>Flight reservation</term><term>General area</term><term>Georgia institute</term><term>Global affinity</term><term>Hong kong</term><term>Incremental acquisition techniques</term><term>Infrastructure services layer</term><term>International conference</term><term>Invocation</term><term>Large databases</term><term>Large number</term><term>Ontology</term><term>Other approaches</term><term>Other words</term><term>Parallel databases</term><term>Past experience</term><term>Personal information management</term><term>Planning task</term><term>Possible combinations</term><term>Query</term><term>Rank services</term><term>Relevant candidate</term><term>Relevant candidate services</term><term>Relevant contexts</term><term>Rental service</term><term>Routine tasks</term><term>Selection approaches</term><term>Selection component</term><term>Service attributes</term><term>Service capabilities</term><term>Service categories</term><term>Service combinations</term><term>Service composition</term><term>Service discovery engine</term><term>Service infrastructure</term><term>Service ontologies</term><term>Service ontology</term><term>Service operation</term><term>Service properties</term><term>Service schema</term><term>Service selection</term><term>Service selection events</term><term>Service selection techniques</term><term>Service usage history</term><term>Service usage patterns</term><term>Services combination</term><term>Services composition</term><term>Services composition frameworks</term><term>Services discovery</term><term>Services ontologies</term><term>Services selection</term><term>Similar contexts</term><term>Similar services</term><term>Specific task</term><term>State chart</term><term>State charts</term><term>Summary attributes</term><term>System administrator</term><term>Task definition</term><term>Task memories</term><term>Task memory</term><term>Task memory builder agent</term><term>Task memory table</term><term>Travel booking task</term><term>Travel planner</term><term>University lyon</term><term>Usage table</term><term>User</term><term>User agent</term><term>User query</term><term>User task</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Conférence internationale</term><term>Ontologie</term></keywords></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: With the increasing availability of Web services and adoption of services oriented paradigm, there is a growing need to dynamically compose services for realizing complex user tasks. While service composition is itself an important problem, a key issue is also how to support users in selecting the most appropriate compositions of services to fulfill a task. In existing dynamic services selection approaches, combinations of services are repeatedly discovered (e.g., using ontology-based matching techniques) and selected by users whenever needed. To improve their effectiveness, we propose a new technique that provides an efficient access to what is named a “task memory”. A task memory is used to provide users with a context-aware service selection by recommending combinations of services that are most appropriate in a given context. A task memory is formed using the service composition history and their metadata. We present an incremental approach for building the task memory in which we monitor how users use and rank the services. The continuous updates of the task memory over time will result in more fine-tuned recommendations for composite services.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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