QUERY RECOMMENDATIONS AND ITS EVALUATION IN WEB INFORMATION RETRIEVAL
Search Engine retrieves significant and essential information from the web based on query terms given by the user. Due to the lack of background knowledge about the information required, shorter length queries posed by the user, the ambiguity of query keywords and dynamic growth of the web, irreleva...
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doaj-a0131e9a682344eabfb0df5bbeb7b5ed2020-11-24T21:26:28ZengICT Academy of Tamil NaduICTACT Journal on Soft Computing0976-65612229-69562015-04-0153991998QUERY RECOMMENDATIONS AND ITS EVALUATION IN WEB INFORMATION RETRIEVALR. Umagandhi0A.V. Senthil Kumar1Department of Computer Technology, Kongunadu Arts and Science College, IndiaDepartment of Computer Applications, Hindustan College of Arts and Science, IndiaSearch Engine retrieves significant and essential information from the web based on query terms given by the user. Due to the lack of background knowledge about the information required, shorter length queries posed by the user, the ambiguity of query keywords and dynamic growth of the web, irrelevant and redundant results are also retrieved by the search engine. Query recommendations is an important technique which analyze the real search intent of the user and suggests the alternative queries to be used by the user in future to satisfies their information need. The proposed method recommends and ranks the alternative queries and evaluates the ranking order of the recommendations with the help of the ranking measures Normalized Discounted Cumulative Gain (NDCG) and Coefficient of Variance (CV). These measures identify the relationship between the ranking techniques. The proposed strategies are experimentally evaluated using a real time search engine query log.http://ictactjournals.in/paper/IJSC_Paper_10_991-998.pdfQueriesPrefixSpanNDCGCVKappa Measure |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
R. Umagandhi A.V. Senthil Kumar |
spellingShingle |
R. Umagandhi A.V. Senthil Kumar QUERY RECOMMENDATIONS AND ITS EVALUATION IN WEB INFORMATION RETRIEVAL ICTACT Journal on Soft Computing Queries PrefixSpan NDCG CV Kappa Measure |
author_facet |
R. Umagandhi A.V. Senthil Kumar |
author_sort |
R. Umagandhi |
title |
QUERY RECOMMENDATIONS AND ITS EVALUATION IN WEB INFORMATION RETRIEVAL |
title_short |
QUERY RECOMMENDATIONS AND ITS EVALUATION IN WEB INFORMATION RETRIEVAL |
title_full |
QUERY RECOMMENDATIONS AND ITS EVALUATION IN WEB INFORMATION RETRIEVAL |
title_fullStr |
QUERY RECOMMENDATIONS AND ITS EVALUATION IN WEB INFORMATION RETRIEVAL |
title_full_unstemmed |
QUERY RECOMMENDATIONS AND ITS EVALUATION IN WEB INFORMATION RETRIEVAL |
title_sort |
query recommendations and its evaluation in web information retrieval |
publisher |
ICT Academy of Tamil Nadu |
series |
ICTACT Journal on Soft Computing |
issn |
0976-6561 2229-6956 |
publishDate |
2015-04-01 |
description |
Search Engine retrieves significant and essential information from the web based on query terms given by the user. Due to the lack of background knowledge about the information required, shorter length queries posed by the user, the ambiguity of query keywords and dynamic growth of the web, irrelevant and redundant results are also retrieved by the search engine. Query recommendations is an important technique which analyze the real search intent of the user and suggests the alternative queries to be used by the user in future to satisfies their information need. The proposed method recommends and ranks the alternative queries and evaluates the ranking order of the recommendations with the help of the ranking measures Normalized Discounted Cumulative Gain (NDCG) and Coefficient of Variance (CV). These measures identify the relationship between the ranking techniques. The proposed strategies are experimentally evaluated using a real time search engine query log. |
topic |
Queries PrefixSpan NDCG CV Kappa Measure |
url |
http://ictactjournals.in/paper/IJSC_Paper_10_991-998.pdf |
work_keys_str_mv |
AT rumagandhi queryrecommendationsanditsevaluationinwebinformationretrieval AT avsenthilkumar queryrecommendationsanditsevaluationinwebinformationretrieval |
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1725979584043679744 |