TS-LocalRank: A topic similarity local ranking algorithm for re-ranking web search results

Ba Dung Le; Sunita  Prasad

doi:10.1109/ATC.2009.5349536

TS-LocalRank: A topic similarity local ranking algorithm for re-ranking web search results

Ba Dung Le, Sunita Prasad

Computing, Mathematics and Engineering

C-DAC: Centre for Development of Advanced Computing, India

Research output: Book chapter/Published conference paper › Conference paper › peer-review

1 Citation (Scopus)

Abstract

This paper proposes a variant of the PageRank algorithm to apply for re-ranking Web search results. The algorithm (named TS-LocalRank) obtains top N pages from search results of a major search engine, assigns a local rank to each page based on the topic similarity between the Web pages, re-orders the Web pages, and presents the results to users. The objectives of this algorithm are (i) to assign a high local rank to the Web pages which are most relevant to user query, and (ii) to minimize the mean absolute deviation of the similarity between web pages in top search results.

Original language	English
Title of host publication	2009 International Conference on Advanced Technologies for Communications
Pages	197-200
Number of pages	4
ISBN (Electronic)	2162-1039
DOIs	https://doi.org/10.1109/ATC.2009.5349536
Publication status	Published - 08 Dec 2009

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title = "TS-LocalRank: A topic similarity local ranking algorithm for re-ranking web search results",

abstract = "This paper proposes a variant of the PageRank algorithm to apply for re-ranking Web search results. The algorithm (named TS-LocalRank) obtains top N pages from search results of a major search engine, assigns a local rank to each page based on the topic similarity between the Web pages, re-orders the Web pages, and presents the results to users. The objectives of this algorithm are (i) to assign a high local rank to the Web pages which are most relevant to user query, and (ii) to minimize the mean absolute deviation of the similarity between web pages in top search results.",

author = "Le, {Ba Dung} and Sunita Prasad",

year = "2009",

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AU - Le, Ba Dung

AU - Prasad, Sunita

PY - 2009/12/8

Y1 - 2009/12/8

N2 - This paper proposes a variant of the PageRank algorithm to apply for re-ranking Web search results. The algorithm (named TS-LocalRank) obtains top N pages from search results of a major search engine, assigns a local rank to each page based on the topic similarity between the Web pages, re-orders the Web pages, and presents the results to users. The objectives of this algorithm are (i) to assign a high local rank to the Web pages which are most relevant to user query, and (ii) to minimize the mean absolute deviation of the similarity between web pages in top search results.

AB - This paper proposes a variant of the PageRank algorithm to apply for re-ranking Web search results. The algorithm (named TS-LocalRank) obtains top N pages from search results of a major search engine, assigns a local rank to each page based on the topic similarity between the Web pages, re-orders the Web pages, and presents the results to users. The objectives of this algorithm are (i) to assign a high local rank to the Web pages which are most relevant to user query, and (ii) to minimize the mean absolute deviation of the similarity between web pages in top search results.

U2 - 10.1109/ATC.2009.5349536

DO - 10.1109/ATC.2009.5349536

M3 - Conference paper

SN - 2162-1020

SP - 197

EP - 200

BT - 2009 International Conference on Advanced Technologies for Communications

ER -

TS-LocalRank: A topic similarity local ranking algorithm for re-ranking web search results

Abstract

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