Search (17 results, page 1 of 1)

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Abstract

Summaries of the popular engines extrated from the search sites. Summaries are from: AltaVista, Excite, HotBot, InfoSeek, Ultra, Lycos, OpenText Web Index, and Yahoo. Information covered includes Contents, Searching tips, Results, and Update frequency

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Abstract

This article describes the journey from the conception of and vision for a modern search-engine-based search environment to its technological realisation. In doing so, it takes up the thread of an earlier article on this subject, this time from a technical viewpoint. As well as presenting the conceptual considerations of the initial stages, this article will principally elucidate the technological aspects of this journey. The starting point for the deliberations about development of an academic search engine was the experience we gained through the generally successful project "Digital Library NRW", in which from 1998 to 2000-with Bielefeld University Library in overall charge-we designed a system model for an Internet-based library portal with an improved academic search environment at its core. At the heart of this system was a metasearch with an availability function, to which we added a user interface integrating all relevant source material for study and research. The deficiencies of this approach were felt soon after the system was launched in June 2001. There were problems with the stability and performance of the database retrieval system, with the integration of full-text documents and Internet pages, and with acceptance by users, because users are increasingly performing the searches themselves using search engines rather than going to the library for help in doing searches. Since a long list of problems are also encountered using commercial search engines for academic use (in particular the retrieval of academic information and long-term availability), the idea was born for a search engine configured specifically for academic use. We also hoped that with one single access point founded on improved search engine technology, we could access the heterogeneous academic resources of subject-based bibliographic databases, catalogues, electronic newspapers, document servers and academic web pages.

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Abstract

We present an analysis of the Yahoo Buzz Index over a period of 45 weeks. Our key findings are that: (1) It is most common for a search term to show up on the index for one week, followed by two weeks, three weeks, etc. Only two terms persist for all 45 weeks studied - Britney Spears and Jennifer Lopez. Search term longevity follows a power-law distribution or a winner-take-all structure; (2) Most search terms focus on entertainment. Search terms related to serious topics are found less often. The Buzz Index does not necessarily follow the "news cycle"; and, (3) We provide two ways to determine "star power" of various search terms - one that emphasizes staying power on the Index and another that emphasizes rank. In general, the methods lead to dramatically different results. Britney Spears performs well in both methods. We conclude that the data available on the Index is symptomatic of a celebrity-crazed, entertainment-centered culture.

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Abstract

This paper presents a test of the validity of using Google Scholar to evaluate the publications of researchers by comparing the premises on which its search engine, PageRank, is based, to those of Garfield's theory of citation indexing. It finds that the premises are identical and that PageRank and Garfield's theory of citation indexing validate each other.

Date

17.12.2013 11:02:22

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Abstract

Traditional on-line search services such as Dialog, DataStar and Lexis provide a wide range of search features (boolean and proximity operators, truncation, etc). This paper discusses the use of these features for effective searching, and argues that these features are required, regardless of advances in search engine technology. The literature on on-line searching is reviewed, identifying features that searchers find desirable for effective searching. A selective survey of current digital libraries available on the Web was undertaken, identifying which search features are present. The survey indicates that current digital libraries do not implement a wide range of search features. For instance: under half of the examples included controlled vocabulary, under half had proximity searching, only one enabled browsing of term indexes, and none of the digital libraries enable searchers to refine an initial search. Suggestions are made for enhancing the search effectiveness of digital libraries; for instance, by providing a full range of search operators, enabling browsing of search terms, enhancement of records with controlled vocabulary, enabling the refining of initial searches, etc.

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Abstract

Users of web search engines are known to mostly focus on the top ranked results of the search engine result page. While many studies support this well known information seeking pattern only few studies concentrate on the question what users are missing by neglecting lower ranked results. To learn more about the relevance distributions in the so-called long tail we conducted a relevance assessment study with the Million Short long-tail web search engine. While we see a clear difference in the content between the head and the tail of the search engine result list we see no statistical significant differences in the binary relevance judgments and weak significant differences when using graded relevance. The tail contains different but still valuable results. We argue that the long tail can be a rich source for the diversification of web search engine result lists but it needs more evaluation to clearly describe the differences.

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Content

The View From Above Browsing for a particular piece on information on the Web can often feel like being stuck in an unfamiliar part of town walking around at street level looking for a particular store. You know the store is around there somewhere, but your viewpoint at ground level is constrained. What you really want is to get above the streets, hovering half a mile or so up in the air, to see the whole neighbourhood. This kind of birds-eye view function has been memorably described by David D. Clark, Senior Research Scientist at MIT's Laboratory for Computer Science and the Chairman of the Invisible Worlds Protocol Advisory Board, as the missing "up button" on the browser [3] . ET-Map is a nice example of a prototype for Clark's "up-button" view of an information space. The goal of information maps, like ET-Map, is to provide the browser with a sense of the lie of the information landscape, what is where, the location of clusters and hotspots, what is related to what. Ideally, this 'big-picture' all-in-one visual summary needs to fit on a single standard computer screen. ET-Map is one of my favourite examples, but there are many other interesting information maps being developed by other researchers and companies (see inset at the bottom of this page). How does ET-Map work? Here is a sequence of screenshots of a typical browsing session with ET-Map, which ends with access to Web pages on jazz musician Miles Davis. You can also tryout ET-Map for yourself, using a fully working demo on the AI Lab's website [4] . We begin with the top-level map showing forty odd broad entertainment 'subject regions' represented by regularly shaped tiles. Each tile is a visual summary of a group of Web pages with similar content. These tiles are shaded different colours to differentiate them, while labels identify the subject of the tile and the number in brackets telling you how many individual Web page links it contains. ET-Map uses two important, but common-sense, spatial concepts in its organisation and representation of the Web. Firstly, the 'subject regions' size is directly related to the number of Web pages in that category. For example, the 'MUSIC' subject area contains over 11,000 pages and so has a much larger area than the neighbouring area of 'LIVE' which only has 4,300 odd pages. This is intuitively meaningful, as the largest tiles are visually more prominent on the map and are likely to be more significant as they contain the most links. In addition, a second spatial concept, that of neighbourhood proximity, is applied so 'subject regions' closely related in term of content are plotted close to each other on the map. For example, 'FILM' and 'YEAR'S OSCARS', at the bottom left, are neighbours in both semantic and spatial space. This make senses as many things in the real-world are ordered in this way, with things that are alike being spatially close together (e.g. layout of goods in a store, or books in a library). Importantly, ET-Map is also a multi-layer map, with sub-maps showing greater informational resolution through a finer degree of categorization. So for any subject region that contains more than two hundred Web pages, a second-level map, with more detailed categories is generated. This subdivision of information space is repeated down the hierarchy as far as necessary. In the example, the user selected the 'MUSIC' subject region which, not surprisingly, contained many thousands of pages. A second-level map with numerous different music categories is then presented to the user. Delving deeper, the user wants to learn more about jazz music, so clicking on the 'JAZZ' tile leads to a third-level map, a fine-grained map of jazz related Web pages. Finally, selecting the 'MILES DAVIS' subject region leads to more a conventional looking ranking of pages from which the user selects one to download.
ET-Map was created using a sophisticated AI technique called Kohonen self-organizing map, a neural network approach that has been used for automatic analysis and classification of semantic content of text documents like Web pages. I do not pretend to fully understand how this technique works; I tend to think of it as a clever 'black-box' that group together things that are alike [5] . It is a real challenge to automatically classify pages from a very heterogeneous information collection like the Web into categories that will match the conceptions of a typical user. Directories like Yahoo! tend to rely on the skill of human editors to achieve this. ET-Map is an interesting prototype that I think highlights well the potential for a map-based approach to Web browsing. I am surprised none of the major search engines or directories have introduced the option of mapping results. Although, I am sure many are working on ideas. People certainly need all the help they get, as Web growth shows no sign of slowing. Just last month it was reported that the Web had surpassed one billion indexable pages [6].
Research Prototypes Visual SiteMap Developed by Xia Lin, based at the College of Library and Information Science, Drexel University. CVG Cyberspace geography visualization, developed by Luc Girardin, at The Graduate Institute of International Studies, Switzerland. WEBSOM Maps the thousands of articles posted on Usenet newsgroups. It is being developed by researchers at the Neural Networks Research Centre, Helsinki University of Technology in Finland. TreeMaps Developed by Brian Johnson, Ben Shneiderman and colleagues in the Human-Computer Interaction Lab at the University of Maryland. Commercial Information Maps: NewsMaps Provides interactive information landscapes summarizing daily news stories, developed Cartia, Inc. Web Squirrel Creates maps known as information farms. It is developed by Eastgate Systems, Inc. Umap Produces interactive maps of Web searches. Map of the Market An interactive map of the market performance of the stocks of major US corporations developed by SmartMoney.com."

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Abstract

This paper introduces a family of link-based ranking algorithms that propagate page importance through links. In these algorithms there is a damping function that decreases with distance, so a direct link implies more endorsement than a link through a long path. PageRank is the most widely known ranking function of this family. The main objective of this paper is to determine whether this family of ranking techniques has some interest per se, and how different choices for the damping function impact on rank quality and on convergence speed. Even though our results suggest that PageRank can be approximated with other simpler forms of rankings that may be computed more efficiently, our focus is of more speculative nature, in that it aims at separating the kernel of PageRank, that is, link-based importance propagation, from the way propagation decays over paths. We focus on three damping functions, having linear, exponential, and hyperbolic decay on the lengths of the paths. The exponential decay corresponds to PageRank, and the other functions are new. Our presentation includes algorithms, analysis, comparisons and experiments that study their behavior under different parameters in real Web graph data. Among other results, we show how to calculate a linear approximation that induces a page ordering that is almost identical to PageRank's using a fixed small number of iterations; comparisons were performed using Kendall's tau on large domain datasets.

Date

16. 1.2016 10:22:28

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Source

Ariadne. 1999, no.22

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Date

10.11.1996 16:36:22

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Date

16. 1.2016 10:22:28

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Abstract

DAFFODIL is a search system for digital libraries aiming at strategic support during the information search process. From a user point of view this strategic support is mainly implemented by high-level search functions, so-called stratagems, which provide functionality beyond today's digital libraries. Through the tight integration of stratagems and with the federation of heterogeneous digital libraries, DAFFODIL reaches high effects of synergy for information and services. These effects provide high-quality metadata for the searcher through an intuitively controllable user interface. The implementation of stratagems follows a tool-based model.

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Abstract

Directed Query Engines, an emerging class of search engine specifically designed to access distributed resources on the deep web, offer the opportunity to create inexpensive digital libraries. Already, one such engine, Distributed Explorer, has been used to select and assemble high quality information resources and incorporate them into publicly available systems for the physical sciences. By nesting Directed Query Engines so that one query launches several other engines in a cascading fashion, enormous virtual collections may soon be assembled to form a comprehensive information infrastructure for the physical sciences. Once a Directed Query Engine has been configured for a set of information resources, distributed alerts tools can provide patrons with personalized, profile-based notices of recent additions to any of the selected resources. Due to the potentially enormous size and scope of Directed Query Engine applications, consideration must be given to issues surrounding the representation of large quantities of information from multiple, heterogeneous sources.

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Abstract

Swoogle is a crawler-based indexing and retrieval system for the Semantic Web, i.e., for Web documents in RDF or OWL. It extracts metadata for each discovered document, and computes relations between documents. Discovered documents are also indexed by an information retrieval system which can use either character N-Gram or URIrefs as keywords to find relevant documents and to compute the similarity among a set of documents. One of the interesting properties we compute is rank, a measure of the importance of a Semantic Web document.

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Abstract

Sometimes I think that us SEOs could be wonderful characters for a Woody Allen movie: We are stressed, nervous, paranoid, we have a tendency for sudden changes of mood...okay, maybe I am exaggerating a little bit, but that's how we tend to (over)react whenever Google announces something. One thing that doesn't help is the lack of clarity coming from Google, which not only never mentions Hummingbird in any official document (for example, in the post of its 15th anniversary), but has also shied away from details of this epochal update in the "off-the-record" declarations of Amit Singhal. In fact, in some ways those statements partly contributed to the confusion. When Google announces an update-especially one like Hummingbird-the best thing to do is to avoid trying to immediately understand what it really is based on intuition alone. It is better to wait until the dust falls to the ground, recover the original documents, examine those related to them (and any variants), take the time to see the update in action, calmly investigate, and then after all that try to find the most plausible answers.

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Abstract

Page Rank is a topic much discussed by Search Engine Optimisation (SEO) experts. At the heart of PageRank is a mathematical formula that seems scary to look at but is actually fairly simple to understand. Despite this many people seem to get it wrong! In particular "Chris Ridings of www.searchenginesystems.net" has written a paper entitled "PageRank Explained: Everything you've always wanted to know about PageRank", pointed to by many people, that contains a fundamental mistake early on in the explanation! Unfortunately this means some of the recommendations in the paper are not quite accurate. By showing code to correctly calculate real PageRank I hope to achieve several things in this response: - Clearly explain how PageRank is calculated. - Go through every example in Chris' paper, and add some more of my own, showing the correct PageRank for each diagram. By showing the code used to calculate each diagram I've opened myself up to peer review - mostly in an effort to make sure the examples are correct, but also because the code can help explain the PageRank calculations. - Describe some principles and observations on website design based on these correctly calculated examples. Any good web designer should take the time to fully understand how PageRank really works - if you don't then your site's layout could be seriously hurting your Google listings! [Note: I have nothing in particular against Chris. If I find any other papers on the subject I'll try to comment evenly]

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Content

"One of the things I enjoyed the most when I was a reference librarian was the wide range of questions my clients sent my way. What was the original title of the first Godzilla movie? (Gojira, released in 1954) Who said 'I'm as pure as the driven slush'? (Tallulah Bankhead) What percentage of adults have gone to a jazz performance in the last year? (11%) I have found that librarians, speech writers and journalists have one thing in common - we all need to find information on all kinds of topics, and we usually need the answers right now. The following are a few of my favorite sites for finding answers to those there-must-be-an-answer-out-there questions. - For the electronic equivalent to the "ready reference" shelf of resources that most librarians keep hidden behind their desks, check out RefDesk . It is particularly good for answering factual questions - Where do I get the new Windows XP Service Pack? Where is the 386 area code? How do I contact my member of Congress? - Another resource for lots of those quick-fact questions is InfoPlease, the publishers of the Information Please almanac .- Right now, it's full of Olympics data, but it also has links to facts and factoids that you would look up in an almanac, atlas, or encyclopedia. - If you want numbers, start with the Statistical Abstract of the US. This source, produced by the U.S. Census Bureau, gives you everything from the divorce rate by state to airline cost indexes going back to 1980. It is many librarians' secret weapon for pulling numbers together quickly. - My favorite question is "how does that work?" Haven't you ever wondered how they get that Olympic torch to continue to burn while it is being carried by runners from one city to the next? Or how solar sails manage to propel a spacecraft? For answers, check out the appropriately-named How Stuff Works. - For questions about movies, my first resource is the Internet Movie Database. It is easy to search, is such a popular site that mistakes are corrected quickly, and is a fun place to catch trailers of both upcoming movies and those dating back to the 30s. - When I need to figure out who said what, I still tend to rely on the print sources such as Bartlett's Familiar Quotations . No, the current edition is not available on the web, but - and this is the librarian in me - I really appreciate the fact that I not only get the attribution but I also see the source of the quote. There are far too many quotes being attributed to a celebrity, but with no indication of the publication in which the quote appeared. Take, for example, the much-cited quote of Margaret Meade, "Never doubt that a small group of thoughtful committed people can change the world; indeed, it's the only thing that ever has!" Then see the page on the Institute for Intercultural Studies site, founded by Meade, and read its statement that it has never been able to verify this alleged quote from Meade. While there are lots of web-based sources of quotes (see QuotationsPage.com and Bartleby, for example), unless the site provides the original source for the quotation, I wouldn't rely on the citation. Of course, if you have a hunch as to the source of a quote, and it was published prior to 1923, head over to Project Gutenberg , which includes the full text of over 12,000 books that are in the public domain. When I needed to confirm a quotation of the Red Queen in "Through the Looking Glass", this is where I started. - And if you are stumped as to where to go to find information, instead of Googling it, try the Librarians' Index to the Internet. While it is somewhat US-centric, it is a great directory of web resources."