Adaptive information retrieval system based on fuzzy profiling

Obada Alhabashneh; Rahat Iqbal; Faiyaz Doctor; Saad Amin

doi:10.1109/FUZZ-IEEE.2015.7338012

Adaptive information retrieval system based on fuzzy profiling

Obada Alhabashneh
, Rahat Iqbal
, Faiyaz Doctor
, Saad Amin

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

9 Citations (Scopus)

120 Downloads (Pure)

Abstract

The importance of finding relevant information for business and decision making is imperative for both individuals as well as enterprises. In this paper, we present an approach for the development of a fuzzy information retrieval (IR) system. The approach provides a new mechanism for constructing and integrating three relevancy profiles comprising of: a task profile, user profile and document profile, into a unified index, through the use of relevance feedback and fuzzy rule based summarisation. Experiments were performed from which relevance feedback and user queries were captured from 35 users on 20 predefined simulated enterprise search tasks. The captured data set was used to develop the three types of profiles and train the fuzzy system. The system shows 86% performance accuracy in correctly classifying document relevance. The overall performance of the system was evaluated based on standard precision and recall which shows significant improvements in retrieving relevant documents based on user queries.

Original language	English
Title of host publication	2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Publisher	IEEE
Pages	1-8
DOIs	https://doi.org/10.1109/FUZZ-IEEE.2015.7338012
Publication status	Published - 2015
Event	IEEE International Conference on Fuzzy Systems - Istanbul, Turkey Duration: 2 Aug 2015 → 5 Aug 2015

Conference

Conference	IEEE International Conference on Fuzzy Systems
Country/Territory	Turkey
City	Istanbul
Period	2/08/15 → 5/08/15

Bibliographical note

“© © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”

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10.1109/FUZZ-IEEE.2015.7338012

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title = "Adaptive information retrieval system based on fuzzy profiling",

abstract = "The importance of finding relevant information for business and decision making is imperative for both individuals as well as enterprises. In this paper, we present an approach for the development of a fuzzy information retrieval (IR) system. The approach provides a new mechanism for constructing and integrating three relevancy profiles comprising of: a task profile, user profile and document profile, into a unified index, through the use of relevance feedback and fuzzy rule based summarisation. Experiments were performed from which relevance feedback and user queries were captured from 35 users on 20 predefined simulated enterprise search tasks. The captured data set was used to develop the three types of profiles and train the fuzzy system. The system shows 86\% performance accuracy in correctly classifying document relevance. The overall performance of the system was evaluated based on standard precision and recall which shows significant improvements in retrieving relevant documents based on user queries. ",

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AU - Iqbal, Rahat

AU - Doctor, Faiyaz

AU - Amin, Saad

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N2 - The importance of finding relevant information for business and decision making is imperative for both individuals as well as enterprises. In this paper, we present an approach for the development of a fuzzy information retrieval (IR) system. The approach provides a new mechanism for constructing and integrating three relevancy profiles comprising of: a task profile, user profile and document profile, into a unified index, through the use of relevance feedback and fuzzy rule based summarisation. Experiments were performed from which relevance feedback and user queries were captured from 35 users on 20 predefined simulated enterprise search tasks. The captured data set was used to develop the three types of profiles and train the fuzzy system. The system shows 86% performance accuracy in correctly classifying document relevance. The overall performance of the system was evaluated based on standard precision and recall which shows significant improvements in retrieving relevant documents based on user queries.

AB - The importance of finding relevant information for business and decision making is imperative for both individuals as well as enterprises. In this paper, we present an approach for the development of a fuzzy information retrieval (IR) system. The approach provides a new mechanism for constructing and integrating three relevancy profiles comprising of: a task profile, user profile and document profile, into a unified index, through the use of relevance feedback and fuzzy rule based summarisation. Experiments were performed from which relevance feedback and user queries were captured from 35 users on 20 predefined simulated enterprise search tasks. The captured data set was used to develop the three types of profiles and train the fuzzy system. The system shows 86% performance accuracy in correctly classifying document relevance. The overall performance of the system was evaluated based on standard precision and recall which shows significant improvements in retrieving relevant documents based on user queries.

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ER -

Adaptive information retrieval system based on fuzzy profiling

Abstract

Conference

Bibliographical note

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