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Article
Publication date: 5 November 2018

Xiaojuan Zhang, Shuguang Han and Wei Lu

The purpose of this paper is to predict news intent by exploring contextual and temporal features directly mined from a general search engine query log.

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159

Abstract

Purpose

The purpose of this paper is to predict news intent by exploring contextual and temporal features directly mined from a general search engine query log.

Design/methodology/approach

First, a ground-truth data set with correctly marked news and non-news queries was built. Second, a detailed analysis of the search goals and topics distribution of news/non-news queries was conducted. Third, three news features, that is, the relationship between entity and contextual words extended from query sessions, topical similarity among clicked results and temporal burst point were obtained. Finally, to understand the utilities of the new features and prior features, extensive prediction experiments on SogouQ (a Chinese search engine query log) were conducted.

Findings

News intent can be predicted with high accuracy by using the proposed contextual and temporal features, and the macro average F1 of classification is around 0.8677. Contextual features are more effective than temporal features. All the three new features are useful and significant in improving the accuracy of news intent prediction.

Originality/value

This paper provides a new and different perspective in recognizing queries with news intent without use of such large corpora as social media (e.g. Wikipedia, Twitter and blogs) and news data sets. The research will be helpful for general-purpose search engines to address search intents for news events. In addition, the authors believe that the approaches described here in this paper are general enough to apply to other verticals with dynamic content and interest, such as blog or financial data.

Details

The Electronic Library, vol. 36 no. 5
Type: Research Article
ISSN: 0264-0473

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Article
Publication date: 19 October 2010

Ashish Kathuria, Bernard J. Jansen, Carolyn Hafernik and Amanda Spink

Web search engines are frequently used by people to locate information on the Internet. However, not all queries have an informational goal. Instead of information, some…

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1195

Abstract

Purpose

Web search engines are frequently used by people to locate information on the Internet. However, not all queries have an informational goal. Instead of information, some people may be looking for specific web sites or may wish to conduct transactions with web services. This paper aims to focus on automatically classifying the different user intents behind web queries.

Design/methodology/approach

For the research reported in this paper, 130,000 web search engine queries are categorized as informational, navigational, or transactional using a k‐means clustering approach based on a variety of query traits.

Findings

The research findings show that more than 75 percent of web queries (clustered into eight classifications) are informational in nature, with about 12 percent each for navigational and transactional. Results also show that web queries fall into eight clusters, six primarily informational, and one each of primarily transactional and navigational.

Research limitations/implications

This study provides an important contribution to web search literature because it provides information about the goals of searchers and a method for automatically classifying the intents of the user queries. Automatic classification of user intent can lead to improved web search engines by tailoring results to specific user needs.

Practical implications

The paper discusses how web search engines can use automatically classified user queries to provide more targeted and relevant results in web searching by implementing a real time classification method as presented in this research.

Originality/value

This research investigates a new application of a method for automatically classifying the intent of user queries. There has been limited research to date on automatically classifying the user intent of web queries, even though the pay‐off for web search engines can be quite beneficial.

Details

Internet Research, vol. 20 no. 5
Type: Research Article
ISSN: 1066-2243

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Article
Publication date: 11 August 2020

Xiaojuan Zhang, Xixi Jiang and Jiewen Qin

The purpose of this study is to generate diversified results for temporally ambiguous queries and the candidate queries are ensured to have a high coverage of subtopics…

Abstract

Purpose

The purpose of this study is to generate diversified results for temporally ambiguous queries and the candidate queries are ensured to have a high coverage of subtopics, which are derived from different temporal periods.

Design/methodology/approach

Two novel time-aware query suggestion diversification models are developed by integrating semantics and temporality information involved in queries into two state-of-the-art explicit diversification algorithms (i.e. IA-select and xQuaD), respectively, and then specifying the components on which these two models rely on. Most importantly, first explored is how to explicitly determine query subtopics for each unique query from the query log or clicked documents and then modeling the subtopics into query suggestion diversification. The discussion on how to mine temporal intent behind a query from query log is also followed. Finally, to verify the effectiveness of the proposal, experiments on a real-world query log are conducted.

Findings

Preliminary experiments demonstrate that the proposed method can significantly outperform the existing state-of-the-art methods in terms of producing the candidate query suggestion for temporally ambiguous queries.

Originality/value

This study reports the first attempt to generate query suggestions indicating diverse interested time points to the temporally ambiguous (input) queries. The research will be useful in enhancing users’ search experience through helping them to formulate accurate queries for their search tasks. In addition, the approaches investigated in the paper are general enough to be used in many domains; that is, experimental information retrieval systems, Web search engines, document archives and digital libraries.

Details

The Electronic Library , vol. 38 no. 4
Type: Research Article
ISSN: 0264-0473

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Book part
Publication date: 10 February 2012

Kerstin Denecke

Purpose — Since a couple of years, we are confronted with the phenomenon of information overload. In particular, the web provides a rich source of a variety of information…

Abstract

Purpose — Since a couple of years, we are confronted with the phenomenon of information overload. In particular, the web provides a rich source of a variety of information mainly in textual, i.e. unstructured form. Thus, web search faces new challenges that are how to make the user aware of the variety of content available and how to satisfy users best with such manifold content.

Methodology — This variety of content is considered as diversity, i.e. the reflection of a result set's coverage of multiple interpretations of a query. Diversification within web search aims on the one hand at adapting the ranking in a way that the top results are diverse. Increasingly important becomes on the other hand the organization and classification of content within diversification.

Findings — Various approaches to diversification are available or currently focus on research activities. They range from an adapted ranking by means of similarity measures or diversity scores to a comprehensive diversity analysis which determines topics and classifies text according to opinions etc.

Implications — Given the high diversity of web content, approaches for diversification are extremely important. Web search tries to address this problem from different perspectives. For the future, combination with image search result diversification is important. Further, benchmarks and standard data sets for evaluations need to be established to ensure comparability of results from various approaches.

Originality/value — This chapter provides an overview on diversity in web search from two directions: (a) Diversity is introduced with its notions and dimensions. (b) Methods to assess diversity within web search are presented.

Details

Web Search Engine Research
Type: Book
ISBN: 978-1-78052-636-2

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Article
Publication date: 22 June 2010

Jana Besser, Martha Larson and Katja Hofmann

This research aims to identify users' goals and strategies when searching for podcasts and their impact on the design of podcast retrieval technology. In particular, the…

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1448

Abstract

Purpose

This research aims to identify users' goals and strategies when searching for podcasts and their impact on the design of podcast retrieval technology. In particular, the paper seeks to explore the potential to address user goals with indexing based on podcast metadata and automatic speech recognition (ASR) transcripts.

Design/methodology/approach

The paper conducted a user study to obtain an overview of podcast search behaviour and goals, using a multi‐method approach of an online survey, a diary study, and contextual interviews. In a subsequent podcast retrieval experiment, the paper investigated the retrieval performance of the two choices of indexing features for search goals identified during the study.

Findings

The paper found that study participants used a variety of search strategies, partially influenced by available tools and their perceptions of these tools. Furthermore the experimental results revealed that retrieval using ASR transcripts performed significantly better than metadata‐based searching. However, a detailed result analysis suggested that the efficacy of the indexing methods was search‐goal dependent.

Research limitations/implications

The research constitutes a step towards a future framework for investigating user needs and addressing them in an experimental set‐up. It was primarily qualitative and exploratory in nature.

Practical implications

Podcast search engines require evidence about suitable indexing methods in order to make an informed decision concerning whether it is worth the resources to generate speech recognition transcripts.

Originality/value

Systematic studies of podcast searching have not previously been reported. Investigations of this kind hold the potential to optimise podcast retrieval in the long term.

Details

Online Information Review, vol. 34 no. 3
Type: Research Article
ISSN: 1468-4527

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Article
Publication date: 7 July 2011

Dirk Lewandowski

The purpose of this paper is to test major web search engines on their performance on navigational queries, i.e. searches for homepages.

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4226

Abstract

Purpose

The purpose of this paper is to test major web search engines on their performance on navigational queries, i.e. searches for homepages.

Design/methodology/approach

In total, 100 user queries are posed to six search engines (Google, Yahoo!, MSN, Ask, Seekport, and Exalead). Users described the desired pages, and the results position of these was recorded. Measured success and mean reciprocal rank are calculated.

Findings

The performance of the major search engines Google, Yahoo!, and MSN was found to be the best, with around 90 per cent of queries answered correctly. Ask and Exalead performed worse but received good scores as well.

Research limitations/implications

All queries were in German, and the German‐language interfaces of the search engines were used. Therefore, the results are only valid for German queries.

Practical implications

When designing a search engine to compete with the major search engines, care should be taken on the performance on navigational queries. Users can be influenced easily in their quality ratings of search engines based on this performance.

Originality/value

This study systematically compares the major search engines on navigational queries and compares the findings with studies on the retrieval effectiveness of the engines on informational queries.

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Article
Publication date: 21 March 2016

Zoe Chao

Search engines and web applications have evolved to be more tailored toward individual user’s needs, including the individual’s personal preferences and geographic…

Abstract

Purpose

Search engines and web applications have evolved to be more tailored toward individual user’s needs, including the individual’s personal preferences and geographic location. By integrating the free Google Maps Application Program Interface with locally stored metadata, the author created an interactive map search for users to locate, and navigate to, destinations on the University of New Mexico (UNM) campus. The purpose of this paper is to identify the characteristics of UNM map search queries, the options and prioritization of the metadata augmentation, and the usefulness and possible improvement of the interface.

Design/methodology/approach

Queries, search date/time, and the number of results found were logged and examined. Queries’ search frequency and characteristics were analyzed and categorized.

Findings

From November 1, 2012 to September 15, 2013, the author had a total 14,097 visits to the SearchUNM Maps page (http://search.unm.edu/maps/). There were total 5,868 searches (41 percent of all the page visits), and out of all the search instances, 2,297 of them (39 percent) did not retrieve any results. By analyzing the failed queries, the author was able to develop a strategy to increase successful searches.

Originality/value

Many academic institutions have implemented interactive map searches for users to find locations and navigate on campus. However, to date there is no related research on how users conduct their searches in such a scope. Based on the query analysis, this paper identifies user’s search behavior and discusses the strategies of improving searches results of campus interactive maps.

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Article
Publication date: 13 April 2015

Ahmet Uyar and Farouk Musa Aliyu

The purpose of this paper is to better understand three main aspects of semantic web search engines of Google Knowledge Graph and Bing Satori. The authors investigated…

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1786

Abstract

Purpose

The purpose of this paper is to better understand three main aspects of semantic web search engines of Google Knowledge Graph and Bing Satori. The authors investigated: coverage of entity types, the extent of their support for list search services and the capabilities of their natural language query interfaces.

Design/methodology/approach

The authors manually submitted selected queries to these two semantic web search engines and evaluated the returned results. To test the coverage of entity types, the authors selected the entity types from Freebase database. To test the capabilities of natural language query interfaces, the authors used a manually developed query data set about US geography.

Findings

The results indicate that both semantic search engines cover only the very common entity types. In addition, the list search service is provided for a small percentage of entity types. Moreover, both search engines support queries with very limited complexity and with limited set of recognised terms.

Research limitations/implications

Both companies are continually working to improve their semantic web search engines. Therefore, the findings show their capabilities at the time of conducting this research.

Practical implications

The results show that in the near future the authors can expect both semantic search engines to expand their entity databases and improve their natural language interfaces.

Originality/value

As far as the authors know, this is the first study evaluating any aspect of newly developing semantic web search engines. It shows the current capabilities and limitations of these semantic web search engines. It provides directions to researchers by pointing out the main problems for semantic web search engines.

Details

Online Information Review, vol. 39 no. 2
Type: Research Article
ISSN: 1468-4527

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Article
Publication date: 26 April 2019

Jacqueline Sachse

Web search is more and more moving into mobile contexts. However, screen size of mobile devices is limited and search engine result pages face a trade-off between offering…

Abstract

Purpose

Web search is more and more moving into mobile contexts. However, screen size of mobile devices is limited and search engine result pages face a trade-off between offering informative snippets and optimal use of space. One factor clearly influencing this trade-off is snippet length. The purpose of this paper is to find out what snippet size to use in mobile web search.

Design/methodology/approach

For this purpose, an eye-tracking experiment was conducted showing participants search interfaces with snippets of one, three or five lines on a mobile device to analyze 17 dependent variables. In total, 31 participants took part in the study. Each of the participants solved informational and navigational tasks.

Findings

Results indicate a strong influence of page fold on scrolling behavior and attention distribution across search results. Regardless of query type, short snippets seem to provide too little information about the result, so that search performance and subjective measures are negatively affected. Long snippets of five lines lead to better performance than medium snippets for navigational queries, but to worse performance for informational queries.

Originality/value

Although space in mobile search is limited, this study shows that longer snippets improve usability and user experience. It further emphasizes that page fold plays a stronger role in mobile than in desktop search for attention distribution.

Details

Aslib Journal of Information Management, vol. 71 no. 3
Type: Research Article
ISSN: 2050-3806

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Article
Publication date: 1 April 2005

Margaret Markland

To compare the resource discovery network (RDN) hubs and Google as search tools within an academic context, taking into account well documented user information seeking…

Downloads
1986

Abstract

Purpose

To compare the resource discovery network (RDN) hubs and Google as search tools within an academic context, taking into account well documented user information seeking behaviours. To find out whether the students' apparent preference for search engines as an information retrieval tool means that they might miss quality online resources to support their academic work.

Design/methodology/approach

With key factors about user behaviour and service provision in mind, to conduct a small study to see what students are actually presented with when they search for online information for their academic studies, by comparing search results from the RDN hubs and Google.

Findings

Analysis of results suggests that the exclusive use of search engines will lead to users missing the high quality resources provided by the RDN hubs, that if users use subject gateways in the same way that they use search engines they are likely to miss much that the hubs' sophisticated structures and search options have to offer them, and that search engines do provide access to quality resources.

Research limitations/implications

A larger scale investigation of the level of sophistication of searching behaviour among hubs users is called for.

Practical implications

The study emphasizes the need for online information service developers to take into account well documented user behaviours when designing new services.

Originality/value

The paper will be of value to researchers in the fields of information retrieval and information seeking behaviour, and to developers and providers of online information services to the academic community.

Details

Performance Measurement and Metrics, vol. 6 no. 1
Type: Research Article
ISSN: 1467-8047

Keywords

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