InforLorV4, Main, Merge, bibRecord, 000926

How Case-Based Reasoning on e-Community Knowledge Can Be Improved Thanks to Knowledge Reliability

Identifieur interne : 000926 ( Main/Merge ); précédent : 000925; suivant : 000927

How Case-Based Reasoning on e-Community Knowledge Can Be Improved Thanks to Knowledge Reliability

Auteurs : Emmanuelle Gaillard [France] ; Jean Lieber [France] ; Emmanuel Nauer [France] ; Amélie Cordier [France]

Source :

RBID : Hal:hal-01082369

English descriptors

mix :
- case-basedreasoning, evaluation, feedback, filtering, meta-knowledge, ranking, reliability.

Abstract

This paper shows that performing case-based reasoning (CBR) on knowledge coming from an e-community is improved by taking into account knowledge reliability. MKM (meta-knowledge model) is a model for managing reliability of the knowledge units that are used in the reasoning process. For this, MKM uses meta-knowledge such as belief, trust and reputation, about knowledge units and users. MKM is used both to select relevant knowledge to conduct the reasoning process, and to rank results provided by the CBR engine according to the knowledge reliability. An experiment in which users perform a blind evaluation of results provided by two systems (with and without taking into account reliability, i.e. with and without MKM) shows that users are more satisfied with results provided by the system implementing MKM.

Url:

https://hal.inria.fr/hal-01082369

DOI: 10.1007/978-3-319-11209-1_12

Links toward previous steps (curation, corpus...)

to stream Hal, to step Corpus: 002816
to stream Hal, to step Curation: 002816
to stream Hal, to step Checkpoint: 000860

Links to Exploration step

Hal:hal-01082369

Le document en format XML

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<front><div type="abstract" xml:lang="en">This paper shows that performing case-based reasoning (CBR) on knowledge coming from an e-community is improved by taking into account knowledge reliability. MKM (meta-knowledge model) is a model for managing reliability of the knowledge units that are used in the reasoning process. For this, MKM uses meta-knowledge such as belief, trust and reputation, about knowledge units and users. MKM is used both to select relevant knowledge to conduct the reasoning process, and to rank results provided by the CBR engine according to the knowledge reliability. An experiment in which users perform a blind evaluation of results provided by two systems (with and without taking into account reliability, i.e. with and without MKM) shows that users are more satisfied with results provided by the system implementing MKM.</div>
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How Case-Based Reasoning on e-Community Knowledge Can Be Improved Thanks to Knowledge Reliability

How Case-Based Reasoning on e-Community Knowledge Can Be Improved Thanks to Knowledge Reliability

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