Analysis of Desktop Search and Ranking of Their Results Based on Semantics from User Feedback

Mehul Smriti Raje

doi:10.1109/SITIS.2016.46

Analysis of Desktop Search and Ranking of Their Results Based on Semantics from User Feedback

Mehul Smriti Raje

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

This paper explores the ranking of search results in a desktop search engine. A comparison between web search and desktop search and the respective user behaviour during them, is made. This is followed by an analysis of the existing desktop search tools. The paper then discusses a Bayesian technique to collect user feedback and use it to rank the results of existing search frameworks. The results of evaluation of 449 query-result pairs are reported. It is shown that incorporating user feedback improves the ranking of results by as much as 7.32%.

Original language	English
Title of host publication	Proceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	241-245
Number of pages	5
ISBN (Electronic)	9781509056989
DOIs	https://doi.org/10.1109/SITIS.2016.46
Publication status	Published - 21-04-2017
Externally published	Yes
Event	12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016 - Naples, Italy Duration: 28-11-2016 → 01-12-2016

Conference

Conference	12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016
Country/Territory	Italy
City	Naples
Period	28-11-16 → 01-12-16

All Science Journal Classification (ASJC) codes

Computer Vision and Pattern Recognition
Radiology Nuclear Medicine and imaging
Computer Networks and Communications
Signal Processing

Access to Document

10.1109/SITIS.2016.46

Cite this

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title = "Analysis of Desktop Search and Ranking of Their Results Based on Semantics from User Feedback",

abstract = "This paper explores the ranking of search results in a desktop search engine. A comparison between web search and desktop search and the respective user behaviour during them, is made. This is followed by an analysis of the existing desktop search tools. The paper then discusses a Bayesian technique to collect user feedback and use it to rank the results of existing search frameworks. The results of evaluation of 449 query-result pairs are reported. It is shown that incorporating user feedback improves the ranking of results by as much as 7.32%.",

author = "Raje, {Mehul Smriti}",

year = "2017",

month = apr,

day = "21",

doi = "10.1109/SITIS.2016.46",

language = "English",

pages = "241--245",

booktitle = "Proceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016 ; Conference date: 28-11-2016 Through 01-12-2016",

}

Raje, MS 2017, Analysis of Desktop Search and Ranking of Their Results Based on Semantics from User Feedback. in Proceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016., 7907473, Institute of Electrical and Electronics Engineers Inc., pp. 241-245, 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016, Naples, Italy, 28-11-16. https://doi.org/10.1109/SITIS.2016.46

Analysis of Desktop Search and Ranking of Their Results Based on Semantics from User Feedback. / Raje, Mehul Smriti.

Proceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 241-245 7907473.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - This paper explores the ranking of search results in a desktop search engine. A comparison between web search and desktop search and the respective user behaviour during them, is made. This is followed by an analysis of the existing desktop search tools. The paper then discusses a Bayesian technique to collect user feedback and use it to rank the results of existing search frameworks. The results of evaluation of 449 query-result pairs are reported. It is shown that incorporating user feedback improves the ranking of results by as much as 7.32%.

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BT - Proceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016

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Analysis of Desktop Search and Ranking of Their Results Based on Semantics from User Feedback

Abstract

Conference

All Science Journal Classification (ASJC) codes

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