Fuzzy rule based profiling approach for enterprise information seeking and retrieval

[error in script], 2017. Fuzzy rule based profiling approach for enterprise information seeking and retrieval. Information Sciences, 394-5, pp. 18-37. ISSN 0020-0255

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Abstract

With the exponential growth of information available on the Internet and various organisational intranets there is a need for profile based information seeking and retrieval (IS&R) systems. These systems should be able to support users with their context-aware information needs. This paper presents a new approach for enterprise IS&R systems using fuzzy logic to develop task, user and document profiles to model user information seeking behaviour. Relevance feedback was captured from real users engaged in IS&R tasks. The feedback was used to develop a linear regression model for predicting document relevancy based on implicit relevance indicators. Fuzzy relevance profiles were created using Term Frequency and Inverse Document Frequency (TF/IDF) analysis for the successful user queries. Fuzzy rule based summarisation was used to integrate the three profiles into a unified index reflecting the semantic weight of the query terms related to the task, user and document. The unified index was used to select the most relevant documents and experts related to the query topic. The overall performance of the system was evaluated based on standard precision and recall metrics which show significant improvements in retrieving relevant documents in response to user queries.

Item Type: Journal article
Description: Vol. 394-395
Publication Title: Information Sciences
Creators: Alhabashneh, O., Iqbal, R., Doctor, F. and James, A.
Publisher: Elsevier
Date: July 2017
Volume: 394-5
ISSN: 0020-0255
Identifiers:
NumberType
10.1016/j.ins.2016.12.040DOI
S0020025516322605Publisher Item Identifier
Divisions: Schools > School of Science and Technology
Depositing User: Linda Sullivan
Date Added: 21 Feb 2018 09:38
Last Modified: 21 Feb 2018 09:40
URI: http://irep.ntu.ac.uk/id/eprint/32772

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