Web search engine multimedia functionality

Web search engines are beginning to offer access to multimedia searching, including audio, video and image searching. In this paper we report findings from a study examining the state of multimedia search functionality on major general and specialized Web search engines. We investigated 102 Web search engines to examine: (1) how many Web search engines offer multimedia searching, (2) the type of multimedia search functionality and methods offered, such as “query by example”, and (3) the supports for personalization or customization which are accessible as advanced search. Findings include: (1) few major Web search engines offer multimedia searching and (2) multimedia Web search functionality is generally limited. Our findings show that despite the increasing level of interest in multimedia Web search, those few Web search engines offering multimedia Web search, provide limited multimedia search functionality. Keywords are still the only means of multimedia retrieval, while other methods such as “query by example” are offered by less than 1% of Web search engines examined.     

How are we searching the World Wide Web? A comparison of nine search engine transaction logs

The Web and especially major Web search engines are essential tools in the quest to locate online information for many people. This paper reports results from research that examines characteristics and changes in Web searching from nine studies of five Web search engines based in the US and Europe. We compare interactions occurring between users and Web search engines from the perspectives of session length, query length, query complexity, and content viewed among the Web search engines. The results of our research shows (1) users are viewing fewer result pages, (2) searchers on US-based Web search engines use more query operators than searchers on European-based search engines, (3) there are statistically significant differences in the use of Boolean operators and result pages viewed, and (4) one cannot necessary apply results from studies of one particular Web search engine to another Web search engine. The wide spread use of Web search engines, employment of simple queries, and decreased viewing of result pages may have resulted from algorithmic enhancements by Web search engine companies. We discuss the implications of the findings for the development of Web search engines and design of online content.     

Music search engines: Specifications and challenges

Nowadays we have a proliferation of music data available over the Web. One of the imperative challenges is how to search these vast, global-scale musical resources to find preferred music. Recent research has envisaged the notion of music search engines (MSEs) that allow for searching preferred music over the Web. In this paper, we examine the growing research topic of MSEs, and provide potential specifications to follow and challenges to face.     

Characteristics of character usage in Chinese Web searching

The use of non-English Web search engines has been prevalent. Given the popularity of Chinese Web searching and the unique characteristics of Chinese language, it is imperative to conduct studies with focuses on the analysis of Chinese Web search queries. In this paper, we report our research on the character usage of Chinese search logs from a Web search engine in Hong Kong. By examining the distribution of search query terms, we found that users tended to use more diversified terms and that the usage of characters in search queries was quite different from the character usage of general online information in Chinese. After studying the Zipf distribution of n-grams with different values of n, we found that the curve of unigram is the most curved one of all while the bigram curve follows the Zipf distribution best, and that the curves of n-grams with larger n (n = 3–6) had similar structures with β-values in the range of 0.66–0.86. The distribution of combined n-grams was also studied. All the analyses are performed on the data both before and after the removal of function terms and incomplete terms and similar findings are revealed. We believe the findings from this study have provided some insights into further research in non-English Web searching and will assist in the design of more effective Chinese Web search engines.     

A study of results overlap and uniqueness among major Web search engines

The performance and capabilities of Web search engines is an important and significant area of research. Millions of people world wide use Web search engines very day. This paper reports the results of a major study examining the overlap among results retrieved by multiple Web search engines for a large set of more than 10,000 queries. Previous smaller studies have discussed a lack of overlap in results returned by Web search engines for the same queries. The goal of the current study was to conduct a large-scale study to measure the overlap of search results on the first result page (both non-sponsored and sponsored) across the four most popular Web search engines, at specific points in time using a large number of queries. The Web search engines included in the study were MSN Search, Google, Yahoo! and Ask Jeeves. Our study then compares these results with the first page results retrieved for the same queries by the metasearch engine Dogpile.com. Two sets of randomly selected user-entered queries, one set was 10,316 queries and the other 12,570 queries, from Infospace’s Dogpile.com search engine (the first set was from Dogpile, the second was from across the Infospace Network of search properties were submitted to the four single Web search engines). Findings show that the percent of total results unique to only one of the four Web search engines was 84.9%, shared by two of the three Web search engines was 11.4%, shared by three of the Web search engines was 2.6%, and shared by all four Web search engines was 1.1%. This small degree of overlap shows the significant difference in the way major Web search engines retrieve and rank results in response to given queries. Results point to the value of metasearch engines in Web retrieval to overcome the biases of individual search engines.     

Comparing rankings of search results on the Web

The Web has become an information source for professional data gathering. Because of the vast amounts of information on almost all topics, one cannot systematically go over the whole set of results, and therefore must rely on the ordering of the results by the search engine. It is well known that search engines on the Web have low overlap in terms of coverage. In this study we measure how similar are the rankings of search engines on the overlapping results.We compare rankings of results for identical queries retrieved from several search engines. The method is based only on the set of URLs that appear in the answer sets of the engines being compared. For comparing the similarity of rankings of two search engines, the Spearman correlation coefficient is computed. When comparing more than two sets Kendall’s W is used. These are well-known measures and the statistical significance of the results can be computed. The methods are demonstrated on a set of 15 queries that were submitted to four large Web search engines. The findings indicate that the large public search engines on the Web employ considerably different ranking algorithms.     

Image searching on the Excite Web search engine

A growing body of research is beginning to explore the information-seeking behavior of Web users. The vast majority of these studies have concentrated on the area of textual information retrieval (IR). Little research has examined how people search for non-textual information on the Internet, and few large-scale studies has investigated visual information-seeking behavior with general-purpose Web search engines. This study examined visual information needs as expressed in users’ Web image queries. The data set examined consisted of 1,025,908 sequential queries from 211,058 users of Excite, a major Internet search service. Twenty-eight terms were used to identify queries for both still and moving images, resulting in a subset of 33,149 image queries by 9855 users. We provide data on: (1) image queries – the number of queries and the number of search terms per user, (2) image search sessions – the number of queries per user, modifications made to subsequent queries in a session, and (3) image terms – their rank/frequency distribution and the most highly used search terms. On average, there were 3.36 image queries per user containing an average of 3.74 terms per query. Image queries contained a large number of unique terms. The most frequently occurring image related terms appeared less than 10% of the time, with most terms occurring only once. We contrast this to earlier work by P.G.B. Enser, Journal of Documentation 51 (2) (1995) 126–170, who examined written queries for pictorial information in a non-digital environment. Implications for the development of models for visual information retrieval, and for the design of Web search engines are discussed.     

中外文搜索引擎自然语言问答能力的比较与评价研究

【目的/意义】对Google、Bing、百度和搜狗四个中外文搜索引擎的自然语言问答能力进行评价,以揭示搜 索引擎正在向兼具搜索和自动问答功能的系统演进的趋势,对不同搜索引擎在不同类型问题上的自然语言回答能 力进行比较。【方法/过程】从文本检索会议和自然语言处理与中文计算会议的问答系统评测项目抽取了三类问题 （人物类、时间类、地点类）,并进行搜索,以搜索引擎是否返回准确答案或包含正确答案的精选摘要为标准进行人 工评分,使用单因素方差分析和多重比较检验的方法进行比较分析。【结果/结论】主流的中外文搜索引擎均已具备 一定的自然语言问答能力,但仍存在较大的提升空间。Google总体表现最好,但对于人物类问题的回答能力弱于 搜狗。中外文搜索引擎在时间类问题上的表现均好于人物类和地点类问题。     

Measuring search engine bias

This paper examines a real-time measure of bias in Web search engines. The measure captures the degree to which the distribution of URLs, retrieved in response to a query, deviates from an ideal or fair distribution for that query. This ideal is approximated by the distribution produced by a collection of search engines. Differences between bias and classical retrieval measures are highlighted by examining the possibilities for bias in four extreme cases of recall and precision. The results of experiments examining the influence on bias measurement of subject domains, search engines, and search terms are presented. Three general conclusions are drawn: (1) the performance of search engines can be distinguished with the aid of the bias measure; (2) bias values depend on the subject matter under consideration; (3) choice of search terms does not account for much of the variance in bias values. These conclusions underscore the need to develop “bias profiles” for search engines.     

Discriminating meta-search: a framework for evaluation

There was a proliferation of electronic information sources and search engines in the 1990s. Many of these information sources became available through the ubiquitous interface of the Web browser. Diverse information sources became accessible to information professionals and casual end users alike. Much of the information was also hyperlinked, so that information could be explored by browsing as well as searching. While vast amounts of information were now just a few keystrokes and mouseclicks away, as the choices multiplied, so did the complexity of choosing where and how to look for the electronic information. Much of the complexity in information exploration at the turn of the twenty-first century arose because there was no common cataloguing and control system across the various electronic information sources. In addition, the many search engines available differed widely in terms of their domain coverage, query methods and efficiency.Meta-search engines were developed to improve search performance by querying multiple search engines at once. In principle, meta-search engines could greatly simplify the search for electronic information by selecting a subset of first-level search engines and digital libraries to submit a query to based on the characteristics of the user, the query/topic, and the search strategy. This selection would be guided by diagnostic knowledge about which of the first-level search engines works best under what circumstances. Programmatic research is required to develop this diagnostic knowledge about first-level search engine performance.This paper introduces an evaluative framework for this type of research and illustrates its use in two experiments. The experimental results obtained are used to characterize some properties of leading search engines (as of 1998). Significant interactions were observed between search engine and two other factors (time of day and Web domain). These findings supplement those of earlier studies, providing preliminary information about the complex relationship between search engine functionality and performance in different contexts. While the specific results obtained represent a time-dependent snapshot of search engine performance in 1998, the evaluative framework proposed should be generally applicable in the future.     

The effectiveness of Web search engines for retrieving relevant ecommerce links

Ecommerce is developing into a fast-growing channel for new business, so a strong presence in this domain could prove essential to the success of numerous commercial organizations. However, there is little research examining ecommerce at the individual customer level, particularly on the success of everyday ecommerce searches. This is critical for the continued success of online commerce. The purpose of this research is to evaluate the effectiveness of search engines in the retrieval of relevant ecommerce links. The study examines the effectiveness of five different types of search engines in response to ecommerce queries by comparing the engines’ quality of ecommerce links using topical relevancy ratings. This research employs 100 ecommerce queries, five major search engines, and more than 3540 Web links. The findings indicate that links retrieved using an ecommerce search engine are significantly better than those obtained from most other engines types but do not significantly differ from links obtained from a Web directory service. We discuss the implications for Web system design and ecommerce marketing campaigns.     

Iterative radial basis functions neural networks as metamodels of stochastic simulations of the quality of search engines in the World Wide Web

Stochastic simulation has been very effective in many domains but never applied to the WWW. This study is a premiere in using neural networks in stochastic simulation of the number of rejected Web pages per search query. The evaluation of the quality of search engines should involve not only the resulting set of Web pages but also an estimate of the rejected set of Web pages. The iterative radial basis functions (RBF) neural network developed by Meghabghab and Nasr [Iterative RBF neural networks as meta-models for stochastic simulations, in: Second International Conference on Intelligent Processing and Manufacturing of Materials, IPMM’99, Honolulu, Hawaii, 1999, pp. 729–734] was adapted to the actual evaluation of the number of rejected Web pages on four search engines, i.e., Yahoo, Alta Vista, Google, and Northern Light. Nine input variables were selected for the simulation: (1) precision, (2) overlap, (3) response time, (4) coverage, (5) update frequency, (6) boolean logic, (7) truncation, (8) word and multi-word searching, (9) portion of the Web pages indexed. Typical stochastic simulation meta-modeling uses regression models in response surface methods. RBF becomes a natural target for such an attempt because they use a family of surfaces each of which naturally divides an input space into two regions X+ and X− and the n patterns for testing will be assigned either class X+ or X−. This technique divides the resulting set of responses to a query into accepted and rejected Web pages. To test the hypothesis that the evaluation of any search engine query should involve an estimate of the number of rejected Web pages as part of the evaluation, RBF meta-model was trained on 937 examples from a set of 9000 different simulation runs on the nine different input variables. Results show that two of the variables can be eliminated which include: response time and portion of the Web indexed without affecting evaluation results. Results show that the number of rejected Web pages for a specific set of search queries on these four engines very high. Also a goodness measure of a search engine for a given set of queries can be designed which is a function of the coverage of the search engine and the normalized age of a new document in result set for the query. This study concludes that unless search engine designers address the issue of rejected Web pages, indexing, and crawling, the usage of the Web as a research tool for academic and educational purposes will stay hindered.     

Syntactic complexity of Web search queries through the lenses of language models,networks and users

Across the world, millions of users interact with search engines every day to satisfy their information needs. As the Web grows bigger over time, such information needs, manifested through user search queries, also become more complex. However, there has been no systematic study that quantifies the structural complexity of Web search queries. In this research, we make an attempt towards understanding and characterizing the syntactic complexity of search queries using a multi-pronged approach. We use traditional statistical language modeling techniques to quantify and compare the perplexity of queries with natural language (NL). We then use complex network analysis for a comparative analysis of the topological properties of queries issued by real Web users and those generated by statistical models. Finally, we conduct experiments to study whether search engine users are able to identify real queries, when presented along with model-generated ones. The three complementary studies show that the syntactic structure of Web queries is more complex than what n-grams can capture, but simpler than NL. Queries, thus, seem to represent an intermediate stage between syntactic and non-syntactic communication.     

Mimicking Web search engines for expert search

Many enterprise employees may publish content outside their corporate intranet, making the Web a valuable source for identifying company experts. In this article, we thoroughly investigate the usefulness of Web search engines (WSEs) for expert search. In particular, we claim that the ranking of documentary expertise evidence provided by a WSE should also give an indication of the importance of such evidence. To investigate this, we mimic the rankings of seven different WSEs by trying to reproduce their underlying ranking mechanisms in order to search for candidate experts in the TREC CERC collection. Experimental results show that our approach is effective for expert search, and can significantly improve an intranet-based expert search engine. Moreover, when the mimicking of WSEs is further improved by training, expert search performance is also generally enhanced. Finally, we show that WSEs can be mimicked as effectively using only titles and snippets instead of the full content of WSEs’ results, while drastically reducing network costs.     

Real time search on the web: Queries,topics, and economic value

Real time search is an increasingly important area of information seeking on the Web. In this research, we analyze 1,005,296 user interactions with a real time search engine over a 190 day period. Using query log analysis, we investigate searching behavior, categorize search topics, and measure the economic value of this real time search stream. We examine aggregate usage of the search engine, including number of users, queries, and terms. We then classify queries into subject categories using the Google Directory topical hierarchy. We next estimate the economic value of the real time search traffic using the Google AdWords keyword advertising platform. Results shows that 30% of the queries were unique (used only once in the entire dataset), which is low compared to traditional Web searching. Also, 60% of the search traffic comes from the search engine’s application program interface, indicating that real time search is heavily leveraged by other applications. There are many repeated queries over time via these application program interfaces, perhaps indicating both long term interest in a topic and the polling nature of real time queries. Concerning search topics, the most used terms dealt with technology, entertainment, and politics, reflecting both the temporal nature of the queries and, perhaps, an early adopter user-based. However, 36% of the queries indicate some geographical affinity, pointing to a location-based aspect to real time search. In terms of economic value, we calculate this real time search stream to be worth approximately US $33,000,000 (US $33 M) on the online advertising market at the time of the study. We discuss the implications for search engines and content providers as real time content increasingly enters the main stream as an information source.     

Multitasking during Web search sessions

A user’s single session with a Web search engine or information retrieval (IR) system may consist of seeking information on single or multiple topics, and switch between tasks or multitasking information behavior. Most Web search sessions consist of two queries of approximately two words. However, some Web search sessions consist of three or more queries. We present findings from two studies. First, a study of two-query search sessions on the AltaVista Web search engine, and second, a study of three or more query search sessions on the AltaVista Web search engine. We examine the degree of multitasking search and information task switching during these two sets of AltaVista Web search sessions. A sample of two-query and three or more query sessions were filtered from AltaVista transaction logs from 2002 and qualitatively analyzed. Sessions ranged in duration from less than a minute to a few hours. Findings include: (1) 81% of two-query sessions included multiple topics, (2) 91.3% of three or more query sessions included multiple topics, (3) there are a broad variety of topics in multitasking search sessions, and (4) three or more query sessions sometimes contained frequent topic changes. Multitasking is found to be a growing element in Web searching. This paper proposes an approach to interactive information retrieval (IR) contextually within a multitasking framework. The implications of our findings for Web design and further research are discussed.     

Detecting spam blogs from blog search results

Blogging has been an emerging media for people to express themselves. However, the presence of spam blogs (also known as splogs) may reduce the value of blogs and blog search engines. Hence, splog detection has recently attracted much attention from research. Most existing works on splog detection identify splogs using their content/link features and target on spam filters protecting blog search engines’ index from spam. In this paper, we propose a splog detection framework by monitoring the on-line search results. The novelty of our splog detection is that our detection capitalizes on the results returned by search engines. The proposed method therefore is particularly useful in detecting those splogs that have successfully slipped through the spam filters that are also actively generating spam-posts. More specifically, our method monitors the top-ranked results of a sequence of temporally-ordered queries and detects splogs based on blogs’ temporal behavior. The temporal behavior of a blog is maintained in a blog profile. Given blog profiles, splog detecting functions have been proposed and evaluated using real data collected from a popular blog search engine. Our experiments have demonstrated that splogs could be detected with high accuracy. The proposed method can be implemented on top of any existing blog search engine without intrusion to the latter.     

Evaluating WordBars in exploratory Web search scenarios

Web searchers commonly have difficulties crafting queries to fulfill their information needs; even after they are able to craft a query, they often find it challenging to evaluate the results of their Web searches. Sources of these problems include the lack of support for constructing and refining queries, and the static nature of the list-based representations of Web search results. WordBars has been developed to assist users in their Web search and exploration tasks. This system provides a visual representation of the frequencies of the terms found in the first 100 document surrogates returned from an initial query, in the form of a histogram. Exploration of the search results is supported through term selection in the histogram, resulting in a re-sorting of the search results based on the use of the selected terms in the document surrogates. Terms from the histogram can be easily added or removed from the query, generating a new set of search results. Examples illustrate how WordBars can provide valuable support for query refinement and search results exploration, both when vague and specific initial queries are provided. User evaluations with both expert and intermediate Web searchers illustrate the benefits of the interactive exploration features of WordBars in terms of effectiveness as well as subjective measures. Although differences were found in the demographics of these two user groups, both were able to benefit from the features of WordBars.     

An analysis of Web searching by European AlltheWeb.com users

The Web has become a worldwide source of information and a mainstream business tool. It is changing the way people conduct the daily business of their lives. As these changes are occurring, we need to understand what Web searching trends are emerging within the various global regions. What are the regional differences and trends in Web searching, if any? What is the effectiveness of Web search engines as providers of information? As part of a body of research studying these questions, we have analyzed two data sets collected from queries by mainly European users submitted to AlltheWeb.com on 6 February 2001 and 28 May 2002. AlltheWeb.com is a major and highly rated European search engine. Each data set contains approximately a million queries submitted by over 200,000 users and spans a 24-h period. This longitudinal benchmark study shows that European Web searching is evolving in certain directions. There was some decline in query length, with extremely simple queries. European search topics are broadening, with a notable percentage decline in sexual and pornographic searching. The majority of Web searchers view fewer than five Web documents, spending only seconds on a Web document. Approximately 50% of the Web documents viewed by these European users were topically relevant. We discuss the implications for Web information systems and information content providers.     

国内医学搜索引擎的现状及发展对策

通用搜索引擎没有对医学专业信息进行优化处理，不适合检索专业化的医学信息。因此，为了适应用户需要，加强对医学专业搜索引擎的研究是十分必要的。本文指出了国内医学搜索引擎存在的问题，提出了中文医学搜索引擎改变现状、快速发展的几点对策。