Search (79 results, page 2 of 4)

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Abstract

Imagine a library containing 25 billion documents but with no centralized organization and no librarians. In addition, anyone may add a document at any time without telling anyone. You may feel sure that one of the documents contained in the collection has a piece of information that is vitally important to you, and, being impatient like most of us, you'd like to find it in a matter of seconds. How would you go about doing it? Posed in this way, the problem seems impossible. Yet this description is not too different from the World Wide Web, a huge, highly-disorganized collection of documents in many different formats. Of course, we're all familiar with search engines (perhaps you found this article using one) so we know that there is a solution. This article will describe Google's PageRank algorithm and how it returns pages from the web's collection of 25 billion documents that match search criteria so well that "google" has become a widely used verb. Most search engines, including Google, continually run an army of computer programs that retrieve pages from the web, index the words in each document, and store this information in an efficient format. Each time a user asks for a web search using a search phrase, such as "search engine," the search engine determines all the pages on the web that contains the words in the search phrase. (Perhaps additional information such as the distance between the words "search" and "engine" will be noted as well.) Here is the problem: Google now claims to index 25 billion pages. Roughly 95% of the text in web pages is composed from a mere 10,000 words. This means that, for most searches, there will be a huge number of pages containing the words in the search phrase. What is needed is a means of ranking the importance of the pages that fit the search criteria so that the pages can be sorted with the most important pages at the top of the list. One way to determine the importance of pages is to use a human-generated ranking. For instance, you may have seen pages that consist mainly of a large number of links to other resources in a particular area of interest. Assuming the person maintaining this page is reliable, the pages referenced are likely to be useful. Of course, the list may quickly fall out of date, and the person maintaining the list may miss some important pages, either unintentionally or as a result of an unstated bias. Google's PageRank algorithm assesses the importance of web pages without human evaluation of the content. In fact, Google feels that the value of its service is largely in its ability to provide unbiased results to search queries; Google claims, "the heart of our software is PageRank." As we'll see, the trick is to ask the web itself to rank the importance of pages.

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Abstract

The current web consists of documents that are highly heterogeneous and hard for machines to understand. The Semantic Web is a progressive movement of the Word Wide Web, aiming at converting the current web of unstructured documents to the web of data. In the Semantic Web, web documents are annotated with metadata using standardized ontology language. These annotated documents are directly processable by machines and it highly improves their usability and usefulness. In Ericsson, similar problems occur. There are massive documents being created with well-defined structures. Though these documents are about domain specific knowledge and can have rich relations, they are currently managed by a traditional search engine, which ignores the rich domain specific information and presents few data to users. Motivated by the Semantic Web, we aim to find standard ways to process these documents, extract rich domain specific information and annotate these data to documents with formal markup languages. We propose this project to develop a domain specific search engine for processing different documents and building explicit relations for them. This research project consists of the three main focuses: examining different domain specific documents and finding ways to extract their metadata; integrating a text search engine with an ontology server; exploring novel ways to build relations for documents. We implement this system and demonstrate its functions. As a prototype, the system provides required features and will be extended in the future.

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Abstract

Web search engines, such as Google and Bing, are constantly employing results from knowledge organization and various visualization features to improve their search services. Knowledge graph, a large repository of structured knowledge represented by formal languages such as RDF (Resource Description Framework), is used to support entity search feature of Google and Bing (Demartini, 2016). When a user searchs for an entity, such as a person, an organization, or a place in Google or Bing, it is likely that a knowledge cardwill be presented on the right side bar of the search engine result pages (SERPs). For example, when a user searches the entity Benedict Cumberbatch on Google, the knowledge card will show the basic structured information about this person, including his date of birth, height, spouse, parents, and his movies, etc. The knowledge card, which is used to present the result of entity search, is generated from knowledge graphs. Therefore, the quality of knowledge graphs is essential to the performance of entity search. However, studies on the quality of knowledge graphs from the angle of entity coverage are scant in the literature. This study aims to investigate the coverage of entities of knowledge graphs behind Google and Bing.

Type

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Abstract

In this paper, we discuss the architecture and implementation of the Semantic Web Search Engine (SWSE). Following traditional search engine architecture, SWSE consists of crawling, data enhancing, indexing and a user interface for search, browsing and retrieval of information; unlike traditional search engines, SWSE operates over RDF Web data - loosely also known as Linked Data - which implies unique challenges for the system design, architecture, algorithms, implementation and user interface. In particular, many challenges exist in adopting Semantic Web technologies for Web data: the unique challenges of the Web - in terms of scale, unreliability, inconsistency and noise - are largely overlooked by the current Semantic Web standards. Herein, we describe the current SWSE system, initially detailing the architecture and later elaborating upon the function, design, implementation and performance of each individual component. In so doing, we also give an insight into how current Semantic Web standards can be tailored, in a best-effort manner, for use on Web data. Throughout, we offer evaluation and complementary argumentation to support our design choices, and also offer discussion on future directions and open research questions. Later, we also provide candid discussion relating to the difficulties currently faced in bringing such a search engine into the mainstream, and lessons learnt from roughly six years working on the Semantic Web Search Engine project.

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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.

Theme

Information Gateway

Type

a

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Content

"Let us start with your positive experiences with Google. I have known Google longer than most. At Opera, we were the first to add their search into the browser interface, enabling it directly from the search box and the address field. At that time, Google was an up-and-coming geeky company. I remember vividly meeting with Google's co-founder Larry Page, his relaxed dress code and his love for the Danger device, which he played with throughout our meeting. Later, I met with the other co-founder of Google, Sergey Brin, and got positive vibes. My first impression of Google was that it was a likeable company. Our cooperation with Google was a good one. Integrating their search into Opera helped us deliver a better service to our users and generated revenue that paid the bills. We helped Google grow, along with others that followed in our footsteps and integrated Google search into their browsers. Then the picture for you and for opera darkened. Yes, then things changed. Google increased their proximity with the Mozilla foundation. They also introduced new services such as Google Docs. These services were great, gained quick popularity, but also exposed the darker side of Google. Not only were these services made to be incompatible with Opera, but also encouraged users to switch their browsers. I brought this up with Sergey Brin, in vain. For millions of Opera users to be able to access these services, we had to hide our browser's identity. The browser sniffing situation only worsened after Google started building their own browser, Chrome. ...
How should Google be regulated? We should limit the amount of information that is being collected. In particular we should look at information that is being collected across sites. It should not be legal to combine data from multiple sites and services. The fact that these sites and services are using the same underlying technology does not change the fact that the user's dealings is with a site at a time and each site should not have the right to share the data with others. I believe this the cornerstone of laws in many countries today, but these laws need to be enforced. Data about us is ours alone and it should not be possible to sell it. We should also limit the ability to target users individually. In the past, ads on sites were ads on sites. You might know what kind of users visited a site and you would place tech ads on tech sites and fashion ads on fashion sites. Now the ads follow you individually. That should be made illegal as it uses data collected from multiple sources and invades our privacy. I also believe there should be regulation as to how location data is used and any information related to our mobile devices. In addition, regulators need to be vigilant as to how companies that have monopoly power use their power. That kind of goes without saying. Companies with monopoly powers should not be able to use those powers when competing in an open market or using their monopoly services to limit competition."

Type

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Abstract

In a series of capsule reviews of 20 search engines Sirapyan gives a good overview of the state of Internet search tools. She starts out with a clear discussion of the types of search tools available, the availability of advanced features such as Boolean queries and differences between directories, regular search engines and metasearch engines. It is unclear from the article whether the author and other testers used the same searches across all of the 20 tools but each review clearly outlines perceived strengths and weaknesses, gives tips on the advanced features, if any, of the search tool in question and suggests the types of searches that are most successful. The tools which receive top honors are Google, Northern Light, HotBot and Oingo. Finally, there is an extra sidebar the discusses meta and specialized search tools such as Infozoid and FirstGov. I can't help thinking that the usefulness of this article is related to the fact that Sirapyan is PC Magazine's librarian and goes into greater depth on those features that are of interest to information professionals

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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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Content

"Swoogle, the Semantic web search engine, is a research project carried out by the ebiquity research group in the Computer Science and Electrical Engineering Department at the University of Maryland. It's an engine tailored towards finding documents on the semantic web. The whole research paper is available here. Semantic web is touted as the next generation of online content representation where the web documents are represented in a language that is not only easy for humans but is machine readable (easing the integration of data as never thought possible) as well. And the main elements of the semantic web include data model description formats such as Resource Description Framework (RDF), a variety of data interchange formats (e.g. RDF/XML, Turtle, N-Triples), and notations such as RDF Schema (RDFS), the Web Ontology Language (OWL), all of which are intended to provide a formal description of concepts, terms, and relationships within a given knowledge domain (Wikipedia). And Swoogle is an attempt to mine and index this new set of web documents. The engine performs crawling of semantic documents like most web search engines and the search is available as web service too. The engine is primarily written in Java with the PHP used for the front-end and MySQL for database. Swoogle is capable of searching over 10,000 ontologies and indexes more that 1.3 million web documents. It also computes the importance of a Semantic Web document. The techniques used for indexing are the more google-type page ranking and also mining the documents for inter-relationships that are the basis for the semantic web. For more information on how the RDF framework can be used to relate documents, read the link here. Being a research project, and with a non-commercial motive, there is not much hype around Swoogle. However, the approach to indexing of Semantic web documents is an approach that most engines will have to take at some point of time. When the Internet debuted, there were no specific engines available for indexing or searching. The Search domain only picked up as more and more content became available. One fundamental question that I've always wondered about it is - provided that the search engines return very relevant results for a query - how to ascertain that the documents are indeed the most relevant ones available. There is always an inherent delay in indexing of document. Its here that the new semantic documents search engines can close delay. Experimenting with the concept of Search in the semantic web can only bore well for the future of search technology."

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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

"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."

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Abstract

The desalination industry involves the desalting of sea or brackish water and achieves the purpose of increasing the worls's effective water supply. There are approximately 4.000 desalination Web sites. The six major Internet search engines were used to determine, according to each of the six, the top twenty sites for desalination. Each site was visited and the 120 gross returns were pared down to the final ten - the 'Top Ten'. The Top Ten were then analyzed to determine what it was that made the sites useful and informative. The major attributes were: a) currency (up-to-date); b) search site capability; c) access to articles on desalination; d) newsletters; e) databases; f) product information; g) online conferencing; h) valuable links to other sites; l) communication links; j) site maps; and k) case studies. Reasons for having a Web site and the current status and prospects for Internet commerce are discussed

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Content

Ramana Rao (Inxight, Palo Alto, CA) 7 ± 2 Insights on achieving Effective Information Access Session One: Updates and a twelve month perspective Danny Sullivan (Search Engine Watch, US / England) Portalization and other search trends Carol Tenopir (University of Tennessee) Search realities faced by end users and professional searchers Session Two: Today's search engines and beyond Daniel Hoogterp (Retrieval Technologies, McLean, VA) Effective presentation and utilization of search techniques Rick Kenny (Fulcrum Technologies, Ontario, Canada) Beyond document clustering: The knowledge impact statement Gary Stock (Ingenius, Kalamazoo, MI) Automated change monitoring Gary Culliss (Direct Hit, Wellesley Hills, MA) User popularity ranked search engines Byron Dom (IBM, CA) Automatically finding the best pages on the World Wide Web (CLEVER) Peter Tomassi (LookSmart, San Francisco, CA) Adding human intellect to search technology Session Three: Panel discussion: Human v automated categorization and editing Ev Brenner (New York, NY)- Chairman James Callan (University of Massachusetts, MA) Marc Krellenstein (Northern Light Technology, Cambridge, MA) Dan Miller (Ask Jeeves, Berkeley, CA) Session Four: Updates and a twelve month perspective Steve Arnold (AIT, Harrods Creek, KY) Review: The leading edge in search and retrieval software Ellen Voorhees (NIST, Gaithersburg, MD) TREC update Session Five: Search engines now and beyond Intelligent Agents John Snyder (Muscat, Cambridge, England) Practical issues behind intelligent agents Text summarization Therese Firmin, (Dept of Defense, Ft George G. Meade, MD) The TIPSTER/SUMMAC evaluation of automatic text summarization systems Cross language searching Elizabeth Liddy (TextWise, Syracuse, NY) A conceptual interlingua approach to cross-language retrieval. Video search and retrieval Armon Amir (IBM, Almaden, CA) CueVideo: Modular system for automatic indexing and browsing of video/audio Speech recognition Michael Witbrock (Lycos, Waltham, MA) Retrieval of spoken documents Visualization James A. Wise (Integral Visuals, Richland, WA) Information visualization in the new millennium: Emerging science or passing fashion? Text mining David Evans (Claritech, Pittsburgh, PA) Text mining - towards decision support

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Abstract

Covers 8 of the most popular search engines. Gives a summary of each and has a nice table of features that also briefly lists the pros and cons. Includes a short explanation of Boolean operators too

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Source

Young information scientists. 1(2016), S.13-29

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Abstract

Artikel als Reaktion auf das Angebot von Google: http://scholar.google.com/. Begleitkommentar des Verfassers: Der "Google-Scholar" (http://scholar.google.com/) ist durchaus eine bemerkenswerte Entwicklung von Google, welche die Internet-Suchtechnik voranbringt - zumindest vordergruendig. Der Satz auf der Scholar Startseite "Stand on the shoulders of giants" drueckt es treffend aus: derart gigantische Ressourcen hat eben im Suchmaschinenbereich sonst niemand. Und genau DAS ist der Punkt: das Quasi-Monopol von Google (spaeter u.U. Microsoft) wird dadurch NOCH staerker werden. Ich halte diese Entwicklung fuer bedrohlich. An dieser Stelle ist kein Vorwurf an Google zu richten: dort verhaelt man sich nur so, wie es der Markt verlangt. Der Vorwurf ist dorthin zu richten, wo diese Entwicklung gesehen und ignoriert wird. Ich erlebe es immer wieder, auch in "hochrangigen" Gespraechen, dass als "Argument" gegen alternative Enticklungen vorgebracht wird "was wollt ihr da eigentlich - es gibt doch Google und die sind doch gut". Solche Kurzsichtigkeit ist kaum uebertreffbar. Von der Zeitschrift "Technology Review" des Heise-Verlages (das deutsche Pendant zum MIT-Review) wurde ich gebeten, hierzu einen Artikel zu schreiben. Sie finden diesen Artikel bei Interesse im WWW unter http://suma-ev.de/tech-rev1.html Daraus hat sich eine Diskussion ueber unabhaengige Suchmaschinen ergeben, die ich hier kurz skizzieren moechte: ----------------------------------------------------------------------- Unabhaengige Suchmaschinen sind in einem weiten Spektrum von Moeglichkeiten denkbar: 1. von voellig freien, nicht strukturierten, losen Zusammenschluessen, z.B. auf Peer-to-Peer Basis (a la YACY: http://suma-lab.de/) 2. bis hin zu staatlich gewollter Unabhaengigkeit durch gesetzliche Regelungen (aehnlich der Intention beim oeffentlich-rechtlichen Rundfunk und Fernsehen); Stichwort: oeffentlich-rechtliche Suchmaschine 3. Dazwischen sind Optionen denkbar, die beides kombinieren: eine Vielzahl von Betreibern kleinerer Suchmaschinen (Mini-Sucher), die sich zu Verbuenden organisieren, in denen Organisationen des oeffentlich-rechtlichen Raumes, wie z.B. Bibliotheken und Universitaeten als klassische Wissensvermittler, eine tragende Rolle spielen. 4. Und moeglicherweise sehen SIE noch ganz andere Moeglichkeiten ...?

Content

Text des Artikels: "Wenn der Rohstoff des 21. Jahrhunderts wirklich Information ist, dann unterscheidet er sich grundlegend von seinen Vorgängern Eisenerz und Erdöl: Er verbraucht sich nicht, kann endlos wiederverwertet werden, ist einfach um die ganze Welt transportierbar, und kann sich sogar durch Neuzusammensetzung vermehren. Letztere Eigenschaft, so schön sie zunächst scheint, wird allmählich zur Plage. Die Menge der weltweit vorliegenden Information wächst seit Jahrhunderten stetig. Laut einem Bericht der University of California in Berkeley schafft die Menschheit derzeit ein bis zwei Exabyte (Milliarden Gigabyte) an Information pro Jahr. Dargestellt als Text entspricht das einem Stapel von rund einer Billion dicker Bücher - dessen Höhe etwa die 130-fachen Entfernung Erde-Mond erreichen würde. Die große Herausforderung ist, aus solch gigantischen Informationsmengen das subjektiv Wesentliche - also das Wissen - herauszusuchen. Die Wissensextraktion wird im digitalen Zeitalter zunehmend von Internet-Suchmaschinen übernommen. Sie verarbeiten den Rohstoff Information zu Wissen, kontrollieren und verteilen ihn. Es kann keinem Nutzer ganz geheuer sein, dass diese Schlüsselfunktion der Informationsgesellschaft in die Hände weniger Konzerne gerät: Google hat mit einem Marktanteil von mehr als 80 Prozent in Deutschland ein De-facto-Monopol erreicht, das nun Microsoft mit seiner "MSN Search" angreifen will. Aber diese Alternative weckt schwerlich mehr Vertrauen.
Suchmaschinen-Monopolisten können bestimmen oder kontrollieren, welche Information wann und auf welchen Rechnern verfügbar ist, und in welcher Reihenfolge die Ergebnisse angezeigt werden. Durch Beobachtung der Abrufe können die Unternehmen genaue Profile ihrer Nutzer erstellen. Um die Vormacht der kommerziellen Wissenswächter zu brechen, bedarf es einer freien Suchkultur - so wie das offene Betriebssystem Linux die Welt vor einer reinen Windows-Monokultur bewahrt hat. Immerhin scheint man auch auf staatlicher Seite das Problem des "Information Overkill" erkannt zu haben. Die öffentliche Hand fördert zahlreiche Projekte, die Ordnung in den Datenwust bringen wollen. Doch die meisten davon sind mehr visionär als realistisch. Vom einst so gefeierten "Semantic Web" etwa ist auch nach Jahren kaum Handfestes zu sehen. Kein Wunder: Solche Vorhaben setzen voraus, dass die Daten zunächst eingesammelt und suchgerecht indiziert werden. Mangels freier Software fehlt diese Voraussetzung. Was also ist nötig, um im Informationszeitalter die freie Verfügbarkeit der Ressourcen sicherzustellen? Die Antwort ist die gleiche wie einst für Kohle, Eisen und Öl: eine Vielfalt von Anbietern. Der beste Weg dorthin führt über freie Suchmaschinen-Software, auf welche die Betreiber solcher Maschinen zurückgreifen können. Dann entstünde ganz von selbst ein offener und dynamischer Wettbewerb. Freie Suchmaschinen-Software ist jedoch sehr rar. Es gibt Ansätze dazu in Russland und ein einziges Projekt in den USA (nutch.org). Auch Europa ist weitgehend Ödnis - bis auf den Lichtblick Yacy, ein Vorhaben des Frankfurter Softwarespezialisten Michael Christen. Yacy ist meines Wissen der weltweit einzige proof-of-concept einer strikt dezentralen Peer-to-Peer-Suchmaschine (suma-lab.de:8080"). Um die Suchmaschinen-Landschaft zu beleben, haben nun 13 Forscher, Politiker und Unternehmer den "Gemeinnützigen Verein zur Förderung der Suchmaschinen-Technologie und des freien Wissenszugangs" (kurz: SuMa-eV, suma-ev.de) mit Sitz in Hannover gegründet. Zu den Gründungsmitgliedern gehören der MP3-Erfinder Karlheinz Brandenburg, der Vizepräsident für Forschung der Universität Hannover Wolfgang Ertmer und ich selbst. Ziel des SuMa-eV ist die Etablierung einer auf möglichst viele autarke Systeme verteilten Suchmaschinen-Infrastruktur, die von ihrem Bauprinzip her kaum monopolisierbar ist. Der Kerngedanke dieser Struktur, die sich aus sehr vielen und sehr unterschiedlichen Bausteinen zusammensetzen kann, liegt in der Autarkie der Einzelsysteme: gesellschaftlicher Pluralismus wird netztopologisch abgebildet. Eigentlich wäre es im Interesse und in der Macht des Staats, die Meinungsvielfalt im Netz besser zu sichern. Während er - abgesehen von ein paar hellhörigen Parlamentariern - noch träumerische Visionen pflegt, müssen Initiativen wie SuMa-eV einspringen."

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Date

22. 2.2017 10:16:49

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Abstract

This article describes a scalable system for searching heterogeneous multilingual collections on the World Wide Web. It details a markup language for describing the characteristics of a search engine and its interface, and a protocol for requesting word translations between languages.

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