Web searching in Chinese: A study of a search engine in Hong Kong

Chau, Michael; Fang, Xiao; Yang, Christopher C.

doi:10.1002/asi.20592

Cited by 33 publications

(31 citation statements)

References 38 publications

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“…For instance Chang et al (2010) explored the performance of Chinese search engines on multi-media retrieval. As mentioned earlier Chau et al (2007) found that Chinese search engines are significantly different from English ones in some aspects. Li et al (2005) evaluated and compared five popular Chinese search engines based on a mathematical model they proposed.…”

Section: Evaluation Approachesmentioning

confidence: 94%

Using a Delphi method and the analytic hierarchy process to evaluate Chinese search engines

Zhu

Meng

et al. 2011

Online Information Review

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Purpose -The purpose of this study is to develop an evaluation criteria system for search engines using the Delphi method and the analytic hierarchy process, and to conduct an empirical study on Chinese search engines to verify it. This is because the evaluation criteria in current research rarely considers expert opinions and experience, and seldom calculates the weight of each criterion by quantitative methods. Design/methodology/approach -Expert investigation of the web-based Delphi method was employed to develop the evaluation criteria, and the analytic hierarchy process based on an exponential scale was adopted to calculate the weight of each criterion. An empirical study was designed to test the evaluation criteria system. A total of 12 study participants were invited to evaluate six popular Chinese search engines by means of e-mail questionnaires. All the calculation processes were executed automatically by Java programming. Findings -The indexing structure and search method were the core criteria for evaluating the search engines. Google (using simplified Chinese characters) achieved the best performance among the six typical Chinese search engines. Originality/value -The criteria for search engine evaluation were determined and weighted by the web-based Delphi method and the analytic hierarchy process based on an exponential scale. IntroductionWith the rapid development of the internet, web search engines have become more and more important as an information retrieval tool. Seeking information from search engines is now part of people's work and everyday lives. Every day billions of people use search engines to find information they need. The steps involved in using search engines are very similar across the different search engines. The user simply enters a query (typically one or more keywords) into a search engine and then the search engine returns a ranked list of relevant documents or webpages (Lawrence, 2000). However, since the ranking algorithms of the search engines are different (Ogilvie and Callan, 2003), the results lists for a specific query are not the same across multiple search engines. This yields the question of how to evaluate those search engine services.The current modes of evaluating search engines can be divided into two types based on their choice of participants. The first type is third party evaluation, which refers to the evaluation process undertaken by commercial or academic organisations. This kind of evaluation concentrates more on indices such as web traffic, precision rate, etc. The second type is user self-evaluation, which emphasises the selection of appropriate indices based on users' specific information needs. However there are flaws in both these modes. During the construction of the criteria system, third party evaluation usually ignores the users' factors, while the user self-evaluation is often too subjective to construct a stable evaluation criteria system. Moreover the majority of studies evaluating search engines are conducted in an ASCII (e.g. English) enviro...

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Section: Evaluation Approachesmentioning

confidence: 94%

Using a Delphi method and the analytic hierarchy process to evaluate Chinese search engines

Zhu

Meng

et al. 2011

Online Information Review

View full text Add to dashboard Cite

show abstract

“…(For a comprehensive review, see Markey, 2007aMarkey, , 2007b.) Additionally, Chau, Fang, and Yang (2007) present results from the analysis of the search logs from Timway, a Chinese search engine, reporting that search topics and the mean number of queries per sessions are similar to usage of English search engines. Whittle, Eaglestone, Ford, Gillet, and Madden (2007) have explored new ways to mine value from search logs.…”

Section: Review Of Literaturementioning

confidence: 98%

Identification of factors predicting clickthrough in Web searching using neural network analysis

Zhang

Jansen

Spink

2008

J. Am. Soc. Inf. Sci.

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In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing.

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“…When they type a very general term, the function can offer suggestions to make the queries more specific. When they are facing difficulties in presenting their queries, the function can provide suggestions based on the overall popularity of search strings by other users, which can be extracted from search logs [6]. Hence the suggestions displayed by the system can enable customers to express the products they want to find more effectively.…”

Section: Research Model and Hypotheses Developmentmentioning

confidence: 99%

The Impact of Query Suggestion in E-Commerce Websites

Lee

Chau

2012

Lecture Notes in Business Information Processing

Self Cite

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Abstract. In this paper we propose a research agenda for studying the impact of query suggestion features on cognitive load and customer satisfaction during online shopping in e-commerce websites. Despite the popular use of query suggestion features in search engines and large e-commerce websites such as Amazon.com and eBay, there is little research in this area. Based on a review on prior literature in query suggestion and online shopping, a research model and five hypotheses are posed. A lab experiment is proposed to test the hypotheses and potential implications of the research are discussed.

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Web searching in Chinese: A study of a search engine in Hong Kong

Cited by 33 publications

References 38 publications

Using a Delphi method and the analytic hierarchy process to evaluate Chinese search engines

Using a Delphi method and the analytic hierarchy process to evaluate Chinese search engines

Identification of factors predicting clickthrough in Web searching using neural network analysis

The Impact of Query Suggestion in E-Commerce Websites

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