Interactive search with weak supervision

This work investigates the possible applications of functional clustering algorithms in relevance feedback algorithms for interactive search. A modified version of the Rocchio algorithm for relevance feedback is proposed based off the result of an LGA clustering of the data. The effectiveness of thi...

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Main Author: Wood, Stuart Thomas
Format: Dissertation (University of Nottingham only)
Language:English
Published: 2017
Subjects:
Online Access:https://eprints.nottingham.ac.uk/49106/
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author Wood, Stuart Thomas
author_facet Wood, Stuart Thomas
author_sort Wood, Stuart Thomas
building Nottingham Research Data Repository
collection Online Access
description This work investigates the possible applications of functional clustering algorithms in relevance feedback algorithms for interactive search. A modified version of the Rocchio algorithm for relevance feedback is proposed based off the result of an LGA clustering of the data. The effectiveness of this algorithm is assessed based on simulations using a tiered probabilistic model for user feedback. It is found that the for a poor initial query (one that is far from the users target query in a vector space model), the simulations run with the modified algorithm reach a close vicinity of the target search faster than the standard Rocchio algorithm even when the increased distance between the current query and the options presented is accounted for. A strong inverse relationship is observed between the strength of the linear structures in the data (measured based on the gap statistic of the data set clustered under LGA) and the improvement in search refinement. Data with gap statistic of 0 offers similar performance to the standard Rocchio algorithm once corrected for the increased distance, suggesting that exploiting linear structures in the data can offer more efficient searching.
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format Dissertation (University of Nottingham only)
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language English
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publishDate 2017
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spelling nottingham-491062018-01-17T23:29:28Z https://eprints.nottingham.ac.uk/49106/ Interactive search with weak supervision Wood, Stuart Thomas This work investigates the possible applications of functional clustering algorithms in relevance feedback algorithms for interactive search. A modified version of the Rocchio algorithm for relevance feedback is proposed based off the result of an LGA clustering of the data. The effectiveness of this algorithm is assessed based on simulations using a tiered probabilistic model for user feedback. It is found that the for a poor initial query (one that is far from the users target query in a vector space model), the simulations run with the modified algorithm reach a close vicinity of the target search faster than the standard Rocchio algorithm even when the increased distance between the current query and the options presented is accounted for. A strong inverse relationship is observed between the strength of the linear structures in the data (measured based on the gap statistic of the data set clustered under LGA) and the improvement in search refinement. Data with gap statistic of 0 offers similar performance to the standard Rocchio algorithm once corrected for the increased distance, suggesting that exploiting linear structures in the data can offer more efficient searching. 2017-12-14 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/49106/1/StuartWood_MScDissertation_4267985.pdf Wood, Stuart Thomas (2017) Interactive search with weak supervision. [Dissertation (University of Nottingham only)] LGA Linear Grouping Algorithm Rocchio Relevance Feedback Clustering Functional Clustering Gap Statistic.
spellingShingle LGA
Linear Grouping Algorithm
Rocchio
Relevance Feedback
Clustering
Functional Clustering
Gap Statistic.
Wood, Stuart Thomas
Interactive search with weak supervision
title Interactive search with weak supervision
title_full Interactive search with weak supervision
title_fullStr Interactive search with weak supervision
title_full_unstemmed Interactive search with weak supervision
title_short Interactive search with weak supervision
title_sort interactive search with weak supervision
topic LGA
Linear Grouping Algorithm
Rocchio
Relevance Feedback
Clustering
Functional Clustering
Gap Statistic.
url https://eprints.nottingham.ac.uk/49106/