Temporal Ranking of Search Engine Results

Jatowt, Adam; Kawai, Yukiko; Tanaka, Katsumi

doi:10.1007/11581062_4

Cited by 17 publications

(16 citation statements)

References 11 publications

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“…RTOs for NBA and DBLP Schemas V. RANKING The challenge of capturing effective results of temporal keywords is the selection of temporal objects that have the highest ranking scores (top-k). This problem is studied very well in IR [6], [20]. Incorporating time dimension into ranking models can significantly improve result effectiveness of user intention…”

Section: Definition 3 Related Temporal Objects Results (Rto) Is a Trementioning

confidence: 99%

“…Second type of ranking methods is based on an analysis of document content [17]. Jatowt [20] presented an approach to rank a document by its freshness and relevance. A document is ranked high if it is modified significantly and recently.…”

Section: Related Workmentioning

confidence: 99%

“…We compute this ranking by also taking timestamp of keyword into account. We extend the CT-rank of Jin [20] which addressed the ranking of keywords and its validity time in web pages. However, our granularity is an object not a document.…”

Section: B Abstractimilarity S Kmentioning

confidence: 99%

See 2 more Smart Citations

TX-Kw: An Effective Temporal XML Keyword Search

Bin-Thalab¹,

El-Tazi²,

El-Sharkawi³

2013

IJACSA

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Abstract-Inspired by the great success of information retrieval (IR) style keyword search on the web, keyword search on XML has emerged recently. Existing methods cannot resolve challenges addressed by using keyword search in Temporal XML documents. We propose a way to evaluate temporal keyword search queries over Temporal XML documents. Moreover, we propose a new ranking method based on the time-aware IR ranking methods to rank temporal keyword search queries results. Extensive experiments have been conducted to show the effectiveness of our approach.

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Section: Definition 3 Related Temporal Objects Results (Rto) Is a Trementioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

TX-Kw: An Effective Temporal XML Keyword Search

Bin-Thalab¹,

El-Tazi²,

El-Sharkawi³

2013

IJACSA

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“…Ranking methods based on an analysis of document content are presented in [31,51,74,100,111]. In [74], Li and Croft proposed to incorporate time into a language modeling framework [73,101], called a time-based language model.…”

Section: Time-aware Rankingmentioning

confidence: 99%

“…In this work, they did not explicitly use the contents of documents, but only date metadata. Jatowt et al presented in [51] an approach to rank a document by its freshness and relevance. The method analyzed changed contents between a current version with archived versions, and find a similarity score of changes to a query topic.…”

Section: Time-aware Rankingmentioning

confidence: 99%

Time-aware approaches to information retrieval

Kanhabua

2012

SIGIR Forum

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In this thesis, we address major challenges in searching temporal document collections. In such collections, documents are created and/or edited over time. Examples of temporal document collections are web archives, news archives, blogs, personal emails and enterprise documents. Unfortunately, traditional IR approaches based on term-matching only can give unsatisfactory results when searching temporal document collections. The reason for this is twofold: the contents of documents are strongly time-dependent, i.e., documents are about events happened at particular time periods, and a query representing an information need can be time-dependent as well, i.e., a temporal query.Our contributions in this thesis are different time-aware approaches within three topics in IR: content analysis, query analysis, and retrieval and ranking models. In particular, we aim at improving the retrieval effectiveness by 1) analyzing the contents of temporal document collections, 2) performing an analysis of temporal queries, and 3) explicitly modeling the time dimension into retrieval and ranking.Leveraging the time dimension in ranking can improve the retrieval effectiveness if information about the creation or publication time of documents is available. In this thesis, we analyze the contents of documents in order to determine the time of non-timestamped documents using temporal language models. We subsequently employ the temporal language models for determining the time of implicit temporal queries, and the determined time is used for re-ranking search results in order to improve the retrieval effectiveness.We study the effect of terminology changes over time and propose an approach to handling terminology changes using time-based synonyms. In addition, we propose different methods for predicting the effectiveness of temporal queries, so that a particular query enhancement technique can be performed to improve the overall performance. When the time dimension is incorporated into ranking, documents will be ranked according to both textual and temporal similarity. In this case, time uncertainty should also be taken into account. Thus, we propose a ranking model that considers the time uncertainty, and improve ranking by combining multiple features using learning-to-rank techniques.Through extensive evaluation, we show that our proposed time-aware approaches outperform traditional retrieval methods and improve the retrieval effectiveness in searching temporal document collections.

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A Web Search Method Based on the Temporal Relation of Query Keywords

Kage

Sumiya

2006

Web Information Systems – WISE 2006

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As use of the Web has become more popular, searching for particular content has been refined by allowing users to enter multiple keywords as queries. However, simple combinations of multiple query keywords may not generate satisfactory search results. We therefore propose a search method which automatically combines query keywords to generate queries by extracting the relations among query keywords. This method consists of two Web search processes: one to determine the temporal relations between query keywords, and one to generate queries based on the obtained temporal relations. We discuss these two processes along with experimental results and implementation issues regarding a prototype system.

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Temporal Ranking of Search Engine Results

Cited by 17 publications

References 11 publications

TX-Kw: An Effective Temporal XML Keyword Search

TX-Kw: An Effective Temporal XML Keyword Search

Time-aware approaches to information retrieval

A Web Search Method Based on the Temporal Relation of Query Keywords

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