Dominant user context (DUC) filtering framework for web personalized search

Current search engine performances need to be improved because often the result suggested by search engine are determine the popularity of a given page for its associated keywords but does not match specific user expectations. Previous researches have indicated that only 20% to 45% of the common sea...

Full description

Bibliographic Details
Published in:IEEE Symposium on Wireless Technology and Applications, ISWTA
Main Author: Abdul Kadir N.; Mohd Lokman A.; Ahmad A.
Format: Conference paper
Language:English
Published: 2012
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84873185693&doi=10.1109%2fISWTA.2012.6373862&partnerID=40&md5=1daa3b57742717f9cccc34e857746c09
id 2-s2.0-84873185693
spelling 2-s2.0-84873185693
Abdul Kadir N.; Mohd Lokman A.; Ahmad A.
Dominant user context (DUC) filtering framework for web personalized search
2012
IEEE Symposium on Wireless Technology and Applications, ISWTA


10.1109/ISWTA.2012.6373862
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84873185693&doi=10.1109%2fISWTA.2012.6373862&partnerID=40&md5=1daa3b57742717f9cccc34e857746c09
Current search engine performances need to be improved because often the result suggested by search engine are determine the popularity of a given page for its associated keywords but does not match specific user expectations. Previous researches have indicated that only 20% to 45% of the common search results are relevant. The search becomes harder when the keyword used is a homographic word, and the results have caused user frustration. The work reported in this paper attempt to design Dominant User Context (DUC) Filtering Framework for personalized search in the effort to solve the problem. Literature analysis was performed to identify types of data commonly used for personalized search results. Using the results, this research developed a framework for search result cluster and dominant user contexts, and performed empirical study to validate the framework. The research performed two phases of survey in order to develop search result cluster and test the implementation of DUC. The result provides a novel idea to increase the relevance of search result and contribute to the body of knowledge in Distributed and Parallel Information Retrieval area. The result enables the enhancement of personalized search result by matching the user behavior, interest and ontology of metadata using the search keyword. This contributes to humanizing the search result, in which it will reduce the gap between human and computer. The result also contributes a new conceptual understanding of the types of data commonly used in developing the personalize search result. The developed DUC Filtering Framework provides a foundation in developing the algorithm for searching tools. This algorithm will largely benefit search engine as well as website search function in producing personalized search results. © 2012 IEEE.

23247851
English
Conference paper

author Abdul Kadir N.; Mohd Lokman A.; Ahmad A.
spellingShingle Abdul Kadir N.; Mohd Lokman A.; Ahmad A.
Dominant user context (DUC) filtering framework for web personalized search
author_facet Abdul Kadir N.; Mohd Lokman A.; Ahmad A.
author_sort Abdul Kadir N.; Mohd Lokman A.; Ahmad A.
title Dominant user context (DUC) filtering framework for web personalized search
title_short Dominant user context (DUC) filtering framework for web personalized search
title_full Dominant user context (DUC) filtering framework for web personalized search
title_fullStr Dominant user context (DUC) filtering framework for web personalized search
title_full_unstemmed Dominant user context (DUC) filtering framework for web personalized search
title_sort Dominant user context (DUC) filtering framework for web personalized search
publishDate 2012
container_title IEEE Symposium on Wireless Technology and Applications, ISWTA
container_volume
container_issue
doi_str_mv 10.1109/ISWTA.2012.6373862
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84873185693&doi=10.1109%2fISWTA.2012.6373862&partnerID=40&md5=1daa3b57742717f9cccc34e857746c09
description Current search engine performances need to be improved because often the result suggested by search engine are determine the popularity of a given page for its associated keywords but does not match specific user expectations. Previous researches have indicated that only 20% to 45% of the common search results are relevant. The search becomes harder when the keyword used is a homographic word, and the results have caused user frustration. The work reported in this paper attempt to design Dominant User Context (DUC) Filtering Framework for personalized search in the effort to solve the problem. Literature analysis was performed to identify types of data commonly used for personalized search results. Using the results, this research developed a framework for search result cluster and dominant user contexts, and performed empirical study to validate the framework. The research performed two phases of survey in order to develop search result cluster and test the implementation of DUC. The result provides a novel idea to increase the relevance of search result and contribute to the body of knowledge in Distributed and Parallel Information Retrieval area. The result enables the enhancement of personalized search result by matching the user behavior, interest and ontology of metadata using the search keyword. This contributes to humanizing the search result, in which it will reduce the gap between human and computer. The result also contributes a new conceptual understanding of the types of data commonly used in developing the personalize search result. The developed DUC Filtering Framework provides a foundation in developing the algorithm for searching tools. This algorithm will largely benefit search engine as well as website search function in producing personalized search results. © 2012 IEEE.
publisher
issn 23247851
language English
format Conference paper
accesstype
record_format scopus
collection Scopus
_version_ 1809677913171165184