-
Mowshowitz, A.; Kawaguchi, A.: Measuring search engine bias (2005)
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- Abstract
- 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.
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Hume, C.: Internet search engines and robots : what they are and how to use them (2000)
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- Abstract
- An overview of the Internet is provided. It describes what the Internet is, how and when it was started, and the four main functions it currently offers. It then focuses on the World Wide Web, and in particular robots and search engines. An overview is provided of both robots and search engines, with some examples and illustrations. It concludes with how to choose a search engine for a particular enquiry, gives some hints and tips for Internet searches, and emphasises that good retrieval is achieved not only by good search engines but also by responsible Web mastering which helps to disseminate effectively any Internet published material.
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Chau, M.; Fang, X.; Sheng, O.R.U.: Analysis of the query logs of a Web site search engine (2005)
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- Abstract
- A large number of studies have investigated the transaction log of general-purpose search engines such as Excite and AItaVista, but few studies have reported an the analysis of search logs for search engines that are limited to particular Web sites, namely, Web site search engines. In this article, we report our research an analyzing the search logs of the search engine of the Utah state government Web site. Our results show that some statistics, such as the number of search terms per query, of Web users are the same for general-purpose search engines and Web site search engines, but others, such as the search topics and the terms used, are considerably different. Possible reasons for the differences include the focused domain of Web site search engines and users' different information needs. The findings are useful for Web site developers to improve the performance of their services provided an the Web and for researchers to conduct further research in this area. The analysis also can be applied in e-government research by investigating how information should be delivered to users in government Web sites.
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Vaughan, L.; Thelwall, M.: Search engine coverage bias : evidence and possible causes (2004)
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- Abstract
- Commercial search engines are now playing an increasingly important role in Web information dissemination and access. Of particular interest to business and national governments is whether the big engines have coverage biased towards the US or other countries. In our study we tested for national biases in three major search engines and found significant differences in their coverage of commercial Web sites. The US sites were much better covered than the others in the study: sites from China, Taiwan and Singapore. We then examined the possible technical causes of the differences and found that the language of a site does not affect its coverage by search engines. However, the visibility of a site, measured by the number of links to it, affects its chance to be covered by search engines. We conclude that the coverage bias does exist but this is due not to deliberate choices of the search engines but occurs as a natural result of cumulative advantage effects of US sites on the Web. Nevertheless, the bias remains a cause for international concern.
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Ding, C.; Patra, J.C.: User modeling for personalized Web search with Self-Organizing Map (2007)
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- Abstract
- The widely used Web search engines index and recommend individual Web pages in response to a few keywords queries to assist users in locating relevant documents. However, the Web search engines give different users the same answer set, although the users may have different preferences. A personalized Web search would carry out the search for each user according to his or her preferences. To conduct the personalized Web search, the authors provide a novel approach to model the user profile with a self-organizing map (SOM). Their results indicate that SOM is capable of helping the user to find the related category for each query used in the Web search to make a personalized Web search effective.
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Spink, A.; Jansen, B.J.; Pedersen , J.: Searching for people on Web search engines (2004)
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- Abstract
- The Web is a communication and information technology that is often used for the distribution and retrieval of personal information. Many people and organizations mount Web sites containing large amounts of information on individuals, particularly about celebrities. However, limited studies have examined how people search for information on other people, using personal names, via Web search engines. Explores the nature of personal name searching on Web search engines. The specific research questions addressed in the study are: "Do personal names form a major part of queries to Web search engines?"; "What are the characteristics of personal name Web searching?"; and "How effective is personal name Web searching?". Random samples of queries from two Web search engines were analyzed. The findings show that: personal name searching is a common but not a major part of Web searching with few people seeking information on celebrities via Web search engines; few personal name queries include double quotations or additional identifying terms; and name searches on Alta Vista included more advanced search features relative to those on AlltheWeb.com. Discusses the implications of the findings for Web searching and search engines, and further research.
-
Jansen, B.J.; Molina, P.R.: ¬The effectiveness of Web search engines for retrieving relevant ecommerce links (2006)
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- Abstract
- 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.
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Entlich, R.: FAQ: Image Search Engines (2001)
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- Abstract
- Everyone loves images. The web wasn't anything until images came along, then it was an overnight success. So how does one find a specific image on the web? By using one of a burgeoning number of image-focused search engines. These search engines are simply optimized versions of typical web indexes, with crawlers that go around sucking down web content and indexing it. But with image search engines, they focus on images only, and the web page text that may describe them. As information professionals, we know that this is a clumsy approach at best, but as the author puts it, until more sophisticated methods become available, the tools profiled here will "have to suffice." Seven search engines are thoroughly tested in this review article, with Google's Image Search (http://www.google.com/imghp?hl=en) being the highest rated
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Hock, R.: ¬A new era of search engines : not just Web pages anymore (2002)
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-
Bradley, P.: ¬The relevance of underpants to searching the Web (2000)
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- Footnote
- Auch unter: http://www.ariadne.ac.uk/issue24/search-engines
-
Sugiura, A.; Etzioni, O.: Query routing for Web search engines : architecture and experiments (2000)
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-
King, D.: Specialized search engines : alternatives to the big guys (2000)
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-
Hock, R.: ¬The latest field trip : an update on field searching in Web search engines (2004)
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-
Zhang, J.; Dimitroff, A.: Internet search engines' response to Metadata Dublin Core implementation (2005)
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Bar-Ilan, J.; Gutman,T.: How do search engines respond to some non-English queries? (2005)
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Notess, G.R.: On the net : dead search engines (2002)
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- Abstract
- Let us sit upon the ground and tell sad stories of the death of ... search engines. That's the gist of this postmortem on the search engines of yore, many quite popular at the time, their names still familiar to our ear. The author, ending on a positive note, points to a list of survivors but still you wonder what will happen if Google ever tanks or goes the "pay-for-positioning" route. Stranger things have happened
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Munson, K.I.: Internet search engines : understanding their design to improve information retrieval (2000)
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- Abstract
- The relationship between the methods currently used for indexing the World Wide Web and the programs, languages, and protocols on which the World Wide Web is based is examined. Two methods for indexing the Web are described, directories being briefly discussed while search engines are considered in detail. The automated approach used to create these tools is examined with special emphasis on the parts of a document used in indexing. Shortcomings of the approach are described. Suggestions for effective use of Web search engines are given
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Stock, W.G.: On relevance distributions (2006)
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- Abstract
- There are at least three possible ways that documents are distributed by relevance: informetric (power law), inverse logistic, and dichotomous. The nature of the type of distribution has implications for the construction of relevance ranking algorithms for search engines, for automated (blind) relevance feedback, for user behavior when using Web search engines, for combining of outputs of search engines for metasearch, for topic detection and tracking, and for the methodology of evaluation of information retrieval systems.
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Edelman, B.: Assessing and improving the safety of Internet search engines (2007)
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- Abstract
- Where Internet users go, attackers follow. Users embrace e-mail; then spammers fill their inboxes with junk mail. With the rise in online commerce, phishers trick them into giving up their passwords. Users find handy downloadable applications; adware vendors bundle them with pop-up-spewing add-ons. The rise of Internet search brings a new type of risk. Hostile Web sites might seek to harm users or take advantage of them - whether through spyware, spam, scams, or other bad practices - because search engines often do not filter these sites from their results. Consider this scenario: Suzy wants to perform Beyonce's Crazy in Love for her school talent show. To make sure she dresses the part, she performs a Google search for >celebrity photos<. When she clicks the first search result, celebritypictures.duble.com, she is quickly prompted to install an adware-bundled ActiveX control in order to browse the site's contents. Eager to view photos of her celebrity role model, she accepts the installation of a new browser toolbar and a pop-up serving adware program. In principle, search engines' listing rules, ranking rules, and advertising policies might shield users from some bad practices, and users' good judgment could protect them from others. But empirically, search engines often lead users to dangerous content. My analysis of search engine safety finds bad practices among approximately 5% of search results for popular keywords, or roughly one site per page of search results.
- Source
- Macht der Suchmaschinen: The Power of Search Engines. Hrsg.: Machill, M. u. M. Beiler
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Wills, R.S.: Google's PageRank : the math behind the search engine (2006)
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- Abstract
- Approximately 91 million American adults use the Internet on a typical day The number-one Internet activity is reading and writing e-mail. Search engine use is next in line and continues to increase in popularity. In fact, survey findings indicate that nearly 60 million American adults use search engines on a given day. Even though there are many Internet search engines, Google, Yahoo!, and MSN receive over 81% of all search requests. Despite claims that the quality of search provided by Yahoo! and MSN now equals that of Google, Google continues to thrive as the search engine of choice, receiving over 46% of all search requests, nearly double the volume of Yahoo! and over four times that of MSN. I use Google's search engine on a daily basis and rarely request information from other search engines. One day, I decided to visit the homepages of Google. Yahoo!, and MSN to compare the quality of search results. Coffee was on my mind that day, so I entered the simple query "coffee" in the search box at each homepage. Table 1 shows the top ten (unsponsored) results returned by each search engine. Although ordered differently, two webpages, www.peets.com and www.coffeegeek.com, appear in all three top ten lists. In addition, each pairing of top ten lists has two additional results in common. Depending on the information I hoped to obtain about coffee by using the search engines, I could argue that any one of the three returned better results: however, I was not looking for a particular webpage, so all three listings of search results seemed of equal quality. Thus, I plan to continue using Google. My decision is indicative of the problem Yahoo!, MSN, and other search engine companies face in the quest to obtain a larger percentage of Internet search volume. Search engine users are loyal to one or a few search engines and are generally happy with search results. Thus, as long as Google continues to provide results deemed high in quality, Google likely will remain the top search engine. But what set Google apart from its competitors in the first place? The answer is PageRank. In this article I explain this simple mathematical algorithm that revolutionized Web search.
