-
Calishain, T.; Dornfest, R.; Adam, D.J.: Google Pocket Guide (2003)
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- LCSH
- Google / Handbooks, manuals, etc.
Web search engines / Handbooks, manuals, etc.
Internet searching / Handbooks, manuals, etc.
- Subject
- Google / Handbooks, manuals, etc.
Web search engines / Handbooks, manuals, etc.
Internet searching / Handbooks, manuals, etc.
-
Sherman, C.: Google power : Unleash the full potential of Google (2005)
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- LCSH
- Internet searching / Handbooks, manuals, etc
- Subject
- Internet searching / Handbooks, manuals, etc
-
Li, L.; Shang, Y.; Zhang, W.: Improvement of HITS-based algorithms on Web documents
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- Content
- Vgl.: http%3A%2F%2Fdelab.csd.auth.gr%2F~dimitris%2Fcourses%2Fir_spring06%2Fpage_rank_computing%2Fp527-li.pdf. Vgl. auch: http://www2002.org/CDROM/refereed/643/.
-
Park, E.-K.; Ra, D.-Y.; Jang, M.-G.: Techniques for improving web retrieval effectiveness (2005)
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- Abstract
- This paper talks about several schemes for improving retrieval effectiveness that can be used in the named page finding tasks of web information retrieval (Overview of the TREC-2002 web track. In: Proceedings of the Eleventh Text Retrieval Conference TREC-2002, NIST Special Publication #500-251, 2003). These methods were applied on top of the basic information retrieval model as additional mechanisms to upgrade the system. Use of the title of web pages was found to be effective. It was confirmed that anchor texts of incoming links was beneficial as suggested in other works. Sentence-query similarity is a new type of information proposed by us and was identified to be the best information to take advantage of. Stratifying and re-ranking the retrieval list based on the maximum count of index terms in common between a sentence and a query resulted in significant improvement of performance. To demonstrate these facts a large-scale web information retrieval system was developed and used for experimentation.
- Date
- 26.12.2007 20:28:29
-
Bradley, P.: Advanced Internet searcher's handbook (1998)
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- LCSH
- World Wide Web (Information retrieval system)
Information retrieval
- Subject
- World Wide Web (Information retrieval system)
Information retrieval
-
Garcés, P.J.; Olivas, J.A.; Romero, F.P.: Concept-matching IR systems versus word-matching information retrieval systems : considering fuzzy interrelations for indexing Web pages (2006)
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- Abstract
- This article presents a semantic-based Web retrieval system that is capable of retrieving the Web pages that are conceptually related to the implicit concepts of the query. The concept of concept is managed from a fuzzy point of view by means of semantic areas. In this context, the proposed system improves most search engines that are based on matching words. The key of the system is to use a new version of the Fuzzy Interrelations and Synonymy-Based Concept Representation Model (FIS-CRM) to extract and represent the concepts contained in both the Web pages and the user query. This model, which was integrated into other tools such as the Fuzzy Interrelations and Synonymy based Searcher (FISS) metasearcher and the fz-mail system, considers the fuzzy synonymy and the fuzzy generality interrelations as a means of representing word interrelations (stored in a fuzzy synonymy dictionary and ontologies). The new version of the model, which is based on the study of the cooccurrences of synonyms, integrates a soft method for disambiguating word senses. This method also considers the context of the word to be disambiguated and the thematic ontologies and sets of synonyms stored in the dictionary.
- Date
- 22. 7.2006 17:14:12
- Footnote
- Beitrag in einer Special Topic Section on Soft Approaches to Information Retrieval and Information Access on the Web
-
Hancock, B.: Subject-specific search engines : using the Harvest system to gather and maintain information on the Internet (1998)
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- Abstract
- The increasing expansion of the Internet has made resources available to users in sometimes unmanageable abundance. To help users manage this proliferation of information, librarians have begun to add URLs to their home pages. As well, specialized search engines are being used to retrieve information from selected sources in aneffort to return pertinent results. Describes the Harvest system which has been used to develop Index Antiquus, a specialized engine, for the classics and mediaeval studies. Presents a working example of how to search Index Antiquus
- Date
- 6. 3.1997 16:22:15
5. 3.1999 19:29:26
-
Mukherjea, S.; Hirata, K.; Hara, Y.: Towards a multimedia World-Wide Web information retrieval engine (1997)
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- Abstract
- Describes a search engine that integrate text and image search. 1 or more Web site can be indexed for both textual and image information, allowing the user to search based on keywords or images or both. Another problem with the current search engines is that they show the results as pages of scrolled lists; this is not very user-friendly. The search engine allows the user to visualise to results in various ways. Explains the indexing and searching techniques of the search engine and highlights several features of the querying interface to make the retrieval process more efficient. Use examples to show the usefulness of the technology
- Date
- 1. 8.1996 22:08:06
- Source
- Computer networks and ISDN systems. 29(1997) no.8, S.1181-1191
-
Ardo, A.; Lundberg, S.: ¬A regional distributed WWW search and indexing service : the DESIRE way (1998)
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- Abstract
- Creates an open, metadata aware system for distributed, collaborative WWW indexing. The system has 3 main components: a harvester (for collecting information), a database (for making the collection searchable), and a user interface (for making the information available). all components can be distributed across networked computers, thus supporting scalability. The system is metadata aware and thus allows searches on several fields including title, document author and URL. Nordic Web Index (NWI) is an application using this system to create a regional Nordic Web-indexing service. NWI is built using 5 collaborating service points within the Nordic countries. The NWI databases can be used to build additional services
- Date
- 1. 8.1996 22:08:06
- Theme
- Klassifikationssysteme im Online-Retrieval
-
Chen, L.-C.: Next generation search engine for the result clustering technology (2012)
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- Abstract
- Result clustering has recently attracted a lot of attention to provide the users with a succinct overview of relevant search results than traditional search engines. This chapter proposes a mixed clustering method to organize all returned search results into a hierarchical tree structure. The clustering method accomplishes two main tasks, one is label construction and the other is tree building. This chapter uses precision to measure the quality of clustering results. According to the results of experiments, the author preliminarily concluded that the performance of the system is better than many other well-known commercial and academic systems. This chapter makes several contributions. First, it presents a high performance system based on the clustering method. Second, it develops a divisive hierarchical clustering algorithm to organize all returned snippets into hierarchical tree structure. Third, it performs a wide range of experimental analyses to show that almost all commercial systems are significantly better than most current academic systems.
- Date
- 17. 4.2012 15:22:11
- Source
- Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
-
Chang, C.-H.; Hsu, C.-C.: Customizable multi-engine search tool with clustering (1997)
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- Abstract
- Proposes a new idea of searching under the multi-engine search architecture to overcome the problems associated with relevance ranking. These include clustering of the search results and extraction of co-occurence keywords, which, with the user's feedback, better refines the query in the searching process. The system also provides the construction of the concept space to gradually customize the search tool to fit the usage for the user at the same time
- Date
- 1. 8.1996 22:08:06
- Source
- Computer networks and ISDN systems. 29(1997) no.8, S.1217-1224
-
Smith, A.G.: Search features of digital libraries (2000)
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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.
- Content
- Enthält eine Zusammenstellung der Werkzeuge und Hilfsmittel des Information Retrieval
-
Gossen, T.: Search engines for children : search user interfaces and information-seeking behaviour (2016)
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- Content
- Inhalt: Acknowledgments; Abstract; Zusammenfassung; Contents; List of Figures; List of Tables; List of Acronyms; Chapter 1 Introduction ; 1.1 Research Questions; 1.2 Thesis Outline; Part I Fundamentals ; Chapter 2 Information Retrieval for Young Users ; 2.1 Basics of Information Retrieval; 2.1.1 Architecture of an IR System; 2.1.2 Relevance Ranking; 2.1.3 Search User Interfaces; 2.1.4 Targeted Search Engines; 2.2 Aspects of Child Development Relevant for Information Retrieval Tasks; 2.2.1 Human Cognitive Development; 2.2.2 Information Processing Theory; 2.2.3 Psychosocial Development 2.3 User Studies and Evaluation2.3.1 Methods in User Studies; 2.3.2 Types of Evaluation; 2.3.3 Evaluation with Children; 2.4 Discussion; Chapter 3 State of the Art ; 3.1 Children's Information-Seeking Behaviour; 3.1.1 Querying Behaviour; 3.1.2 Search Strategy; 3.1.3 Navigation Style; 3.1.4 User Interface; 3.1.5 Relevance Judgement; 3.2 Existing Algorithms and User Interface Concepts for Children; 3.2.1 Query; 3.2.2 Content; 3.2.3 Ranking; 3.2.4 Search Result Visualisation; 3.3 Existing Information Retrieval Systems for Children; 3.3.1 Digital Book Libraries; 3.3.2 Web Search Engines 3.4 Summary and DiscussionPart II Studying Open Issues ; Chapter 4 Usability of Existing Search Engines for Young Users ; 4.1 Assessment Criteria; 4.1.1 Criteria for Matching the Motor Skills; 4.1.2 Criteria for Matching the Cognitive Skills; 4.2 Results; 4.2.1 Conformance with Motor Skills; 4.2.2 Conformance with the Cognitive Skills; 4.2.3 Presentation of Search Results; 4.2.4 Browsing versus Searching; 4.2.5 Navigational Style; 4.3 Summary and Discussion; Chapter 5 Large-scale Analysis of Children's Queries and Search Interactions; 5.1 Dataset; 5.2 Results; 5.3 Summary and Discussion Chapter 6 Differences in Usability and Perception of Targeted Web Search Engines between Children and Adults 6.1 Related Work; 6.2 User Study; 6.3 Study Results; 6.4 Summary and Discussion; Part III Tackling the Challenges ; Chapter 7 Search User Interface Design for Children ; 7.1 Conceptual Challenges and Possible Solutions; 7.2 Knowledge Journey Design; 7.3 Evaluation; 7.3.1 Study Design; 7.3.2 Study Results; 7.4 Voice-Controlled Search: Initial Study; 7.4.1 User Study; 7.5 Summary and Discussion; Chapter 8 Addressing User Diversity ; 8.1 Evolving Search User Interface 8.1.1 Mapping Function8.1.2 Evolving Skills; 8.1.3 Detection of User Abilities; 8.1.4 Design Concepts; 8.2 Adaptation of a Search User Interface towards User Needs; 8.2.1 Design & Implementation; 8.2.2 Search Input; 8.2.3 Result Output; 8.2.4 General Properties; 8.2.5 Configuration and Further Details; 8.3 Evaluation; 8.3.1 Study Design; 8.3.2 Study Results; 8.3.3 Preferred UI Settings; 8.3.4 User satisfaction; 8.4 Knowledge Journey Exhibit; 8.4.1 Hardware; 8.4.2 Frontend; 8.4.3 Backend; 8.5 Summary and Discussion; Chapter 9 Supporting Visual Searchers in Processing Search Results 9.1 Related Work
- Date
- 1. 2.2016 18:25:22
- LCSH
- Information storage and retrieval
- Subject
- Information storage and retrieval
-
Carrière, S.J.; Kazman, R.: Webquery : searching and visualising the Web through connectivity (1997)
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- Abstract
- The WebQuery system offers a powerful new method for searching the Web based on connectivity and content. Examines links among the nodes returned in a keyword-based query. Rankes the nodes, giving the highest rank to the most highly connected nodes. By doing so, finds hot spots on the Web that contain information germane to a user's query. WebQuery not only ranks and filters the results of a Web query; it also extends the result set beyond what the search engine retrieves, by finding interesting sites that are highly connected to those sites returned by the original query. Even with WebQuery filering and ranking query results, the result set can be enormous. Explores techniques for visualizing the returned information and discusses the criteria for using each of the technique
- Date
- 1. 8.1996 22:08:06
- Source
- Computer networks and ISDN systems. 29(1997) no.8, S.1257-1267
-
Schaat, S.: Von der automatisierten Manipulation zur Manipulation der Automatisierung (2019)
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- Content
- "Wir kennen das bereits von Google, Facebook und Amazon: Unser Internet-Verhalten wird automatisch erfasst, damit uns angepasste Inhalte präsentiert werden können. Ob uns diese Inhalte gefallen oder nicht, melden wir direkt oder indirekt zurück (Kauf, Klick etc.). Durch diese Feedbackschleife lernen solche Systeme immer besser, was sie uns präsentieren müssen, um unsere Bedürfnisse anzusprechen, und wissen implizit dadurch auch immer besser, wie sie unsere Bedürfniserfüllung - zur Konsumtion - manipulieren können."
- Date
- 19. 2.2019 17:22:00
-
Mostafa, J.: Bessere Suchmaschinen für das Web (2006)
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- Content
- "Seit wenigen Jahren haben Suchmaschinen die Recherche im Internet revolutioniert. Statt in Büchereien zu gehen, um dort mühsam etwas nachzuschlagen, erhalten wir die gewünschten Dokumente heute mit ein paar Tastaturanschlägen und Mausklicks. »Googeln«, nach dem Namen der weltweit dominierenden Suchmaschine, ist zum Synonym für die Online-Recherche geworden. Künftig werden verbesserte Suchmaschinen die gewünschten Informationen sogar noch zielsicherer aufspüren. Die neuen Programme dringen dazu tiefer in die Online-Materie ein. Sie sortieren und präsentieren ihre Ergebnisse besser, und zur Optimierung der Suche merken sie sich die persönlichen Präferenzen der Nutzer, die sie in vorherigen Anfragen ermittelt haben. Zudem erweitern sie den inhaltlichen Horizont, da sie mehr leisten, als nur eingetippte Schlüsselwörter zu verarbeiten. Einige der neuen Systeme berücksichtigen automatisch, an welchem Ort die Anfrage gestellt wurde. Dadurch kann beispielsweise ein PDA (Personal Digital Assistant) über seine Funknetzverbindung das nächstgelegene Restaurant ausfindig machen. Auch Bilder spüren die neuen Suchmaschinen besser auf, indem sie Vorlagen mit ähnlichen, bereits abgespeicherten Mustern vergleichen. Sie können sogar den Namen eines Musikstücks herausfinden, wenn man ihnen nur ein paar Takte daraus vorsummt. Heutige Suchmaschinen basieren auf den Erkenntnissen aus dem Bereich des information retrieval (Wiederfinden von Information), mit dem sich Computerwissenschaftler schon seit über 50 Jahren befassen. Bereits 1966 schrieb Ben Ami Lipetz im Scientific American einen Artikel über das »Speichern und Wiederfinden von Information«. Damalige Systeme konnten freilich nur einfache Routine- und Büroanfragen bewältigen. Lipetz zog den hellsichtigen Schluss, dass größere Durchbrüche im information retrieval erst dann erreichbar sind, wenn Forscher die Informationsverarbeitung im menschlichen Gehirn besser verstanden haben und diese Erkenntnisse auf Computer übertragen. Zwar können Computer dabei auch heute noch nicht mit Menschen mithalten, aber sie berücksichtigen bereits weit besser die persönlichen Interessen, Gewohnheiten und Bedürfnisse ihrer Nutzer. Bevor wir uns neuen Entwicklungen bei den Suchmaschinen zuwenden, ist es hilfreich, sich ein Bild davon zu machen, wie die bisherigen funktionieren: Was genau ist passiert, wenn »Google« auf dem Bildschirm meldet, es habe in 0,32 Sekunden einige Milliarden Dokumente durchsucht? Es würde wesentlich länger dauern, wenn dabei die Schlüsselwörter der Anfrage nacheinander mit den Inhalten all dieser Webseiten verglichen werden müssten. Um lange Suchzeiten zu vermeiden, führen die Suchmaschinen viele ihrer Kernoperationen bereits lange vor dem Zeitpunkt der Nutzeranfrage aus.
An der Wurzel des Indexbaums Im ersten Schritt werden potenziell interessante Inhalte identifiziert und fortlaufend gesammelt. Spezielle Programme vom Typ so genannter Webtrawler können im Internet publizierte Seiten ausfindig machen, durchsuchen (inklusive darauf befindlicher Links) und die Seiten an einem Ort gesammelt speichern. Im zweiten Schritt erfasst das System die relevanten Wörter auf diesen Seiten und bestimmt mit statistischen Methoden deren Wichtigkeit. Drittens wird aus den relevanten Begriffen eine hocheffiziente baumartige Datenstruktur erzeugt, die diese Begriffe bestimmten Webseiten zuordnet. Gibt ein Nutzer eine Anfrage ein, wird nur der gesamte Baum - auch Index genannt - durchsucht und nicht jede einzelne Webseite. Die Suche beginnt an der Wurzel des Indexbaums, und bei jedem Suchschritt wird eine Verzweigung des Baums (die jeweils viele Begriffe und zugehörige Webseiten beinhaltet) entweder weiter verfolgt oder als irrelevant verworfen. Dies verkürzt die Suchzeiten dramatisch. Um die relevanten Fundstellen (oder Links) an den Anfang der Ergebnisliste zu stellen, greift der Suchalgorithmus auf verschiedene Sortierstrategien zurück. Eine verbreitete Methode - die Begriffshäufigkeit - untersucht das Vorkommen der Wörter und errechnet daraus numerische Gewichte, welche die Bedeutung der Wörter in den einzelnen Dokumenten repräsentieren. Häufige Wörter (wie »oder«, »zu«, »mit«), die in vielen Dokumenten auftauchen, erhalten deutlich niedrigere Gewichte als Wörter, die eine höhere semantische Relevanz aufweisen und nur in vergleichsweise wenigen Dokumenten zu finden sind. Webseiten können aber auch nach anderen Strategien indiziert werden. Die Linkanalyse beispielsweise untersucht Webseiten nach dem Kriterium, mit welchen anderen Seiten sie verknüpft sind. Dabei wird analysiert, wie viele Links auf eine Seite verweisen und von dieser Seite selbst ausgehen. Google etwa verwendet zur Optimierung der Suchresultate diese Linkanalyse. Sechs Jahre benötigte Google, um sich als führende Suchmaschine zu etablieren. Zum Erfolg trugen vor allem zwei Vorzüge gegenüber der Konkurrenz bei: Zum einen kann Google extrem große Weberawling-Operationen durchführen. Zum anderen liefern seine Indizierungsund Gewichtungsmethoden überragende Ergebnisse. In letzter Zeit jedoch haben andere Suchmaschinen-Entwickler einige neue, ähnlich leistungsfähige oder gar punktuell bessere Systeme entwickelt.
Viele digitale Inhalte können mit Suchmaschinen nicht erschlossen werden, weil die Systeme, die diese verwalten, Webseiten auf andere Weise speichern, als die Nutzer sie betrachten. Erst durch die Anfrage des Nutzers entsteht die jeweils aktuelle Webseite. Die typischen Webtrawler sind von solchen Seiten überfordert und können deren Inhalte nicht erschließen. Dadurch bleibt ein Großteil der Information - schätzungsweise 500-mal so viel wie das, was das konventionelle Web umfasst - für Anwender verborgen. Doch nun laufen Bemühungen, auch dieses »versteckte Web« ähnlich leicht durchsuchbar zu machen wie seinen bisher zugänglichen Teil. Zu diesem Zweck haben Programmierer eine neuartige Software entwickelt, so genannte Wrapper. Sie macht sich zu Nutze, dass online verfügbare Information standardisierte grammatikalische Strukturen enthält. Wrapper erledigen ihre Arbeit auf vielerlei Weise. Einige nutzen die gewöhnliche Syntax von Suchanfragen und die Standardformate der Online-Quellen, um auf versteckte Inhalte zuzugreifen. Andere verwenden so genannte ApplikationsprogrammSchnittstellen (APIs), die Software in die Lage versetzen, standardisierte Operationen und Befehle auszuführen. Ein Beispiel für ein Programm, das auf versteckte Netzinhalte zugreifen kann, ist der von BrightPlanet entwickelte »Deep Query Manager«. Dieser wrapperbasierte Anfragemanager stellt Portale und Suchmasken für mehr als 70 000 versteckte Webquellen bereit. Wenn ein System zur Erzeugung der Rangfolge Links oder Wörter nutzt, ohne dabei zu berücksichtigen, welche Seitentypen miteinander verglichen werden, besteht die Gefahr des Spoofing: Spaßvögel oder Übeltäter richten Webseiten mit geschickt gewählten Wörtern gezielt ein, um das Rangberechnungssystem in die Irre zu führen. Noch heute liefert die Anfrage nach »miserable failure« (»klägliches Versagen«) an erster Stelle eine offizielle Webseite des Weißen Hauses mit der Biografie von Präsident Bush.
Vorsortiert und radförmig präsentiert Statt einfach nur die gewichtete Ergebnisliste zu präsentieren (die relativ leicht durch Spoofing manipuliert werden kann), versuchen einige Suchmaschinen, unter denjenigen Webseiten, die am ehesten der Anfrage entsprechen, Ähnlichkeiten und Unterschiede zu finden und die Ergebnisse in Gruppen unterteilt darzustellen. Diese Muster können Wörter sein, Synonyme oder sogar übergeordnete Themenbereiche, die nach speziellen Regeln ermittelt werden. Solche Systeme ordnen jeder gefundenen Linkgruppe einen charakteristischen Begriff zu. Der Anwender kann die Suche dann weiter verfeinern, indem er eine Untergruppe von Ergebnissen auswählt. So liefern etwa die Suchmaschinen »Northern Light« (der Pionier auf diesem Gebiet) und »Clusty« nach Gruppen (Clustern) geordnete Ergebnisse. »Mooter«, eine innovative Suchmaschine, die ebenfalls diese Gruppiertechnik verwendet, stellt die Gruppen zudem grafisch dar (siehe Grafik links unten). Das System ordnet die UntergruppenButtons radförmig um einen zentralen Button an, der sämtliche Ergebnisse enthält. Ein Klick auf die UntergruppenButtons erzeugt Listen relevanter Links und zeigt neue, damit zusammenhängende Gruppen. Mooter erinnert sich daran, welche Untergruppen gewählt wurden. Noch genauere Ergebnisse erhält der Nutzer, wenn er die Verfeinerungsoption wählt: Sie kombiniert bei früheren Suchen ausgewählte Gruppen mit der aktuellen Anfrage. Ein ähnliches System, das ebenfalls visuelle Effekte nutzt, ist »Kartoo«. Es handelt sich dabei um eine so genannte Meta-Suchmaschine: Sie gibt die Nutzeranfragen an andere Suchmaschinen weiter und präsentiert die gesammelten Ergebnisse in grafischer Form. Kartoo liefert eine Liste von Schlüsselbegriffen von den unterschiedlichen Webseiten und generiert daraus eine »Landkarte«. Auf ihr werden wichtige Seiten als kons (Symbole) dargestellt und Bezüge zwischen den Seiten mit Labeln und Pfaden versehen. Jedes Label lässt sich zur weiteren Verfeinerung der Suche nutzen. Einige neue Computertools erweitern die Suche dadurch, dass sie nicht nur das Web durchforsten, sondern auch die Festplatte des eigenen Rechners. Zurzeit braucht man dafür noch eigenständige Programme. Aber Google hat beispielsweise kürzlich seine »Desktop Search« angekündigt, die zwei Funktionen kombiniert: Der Anwender kann angeben, ob das Internet, die Festplatte oder beides zusammen durchsucht werden soll. Die nächste Version von Microsoft Windows (Codename »Longhorn«) soll mit ähnlichen Fähigkeiten ausgestattet werden: Longhorn soll die implizite Suche beherrschen, bei der Anwender ohne Eingabe spezifischer Anfragen relevante Informationen auffinden können. (Dabei werden Techniken angewandt, die in einem anderen Microsoft-Projekt namens »Stuff I've seen« - »Sachen, die ich gesehen habe« - entwickelt wurden.) Bei der impliziten Suche werden Schlüsselwörter aus der Textinformation gewonnen, die der Anwender in jüngster Zeit auf dem Rechner verarbeitet oder verändert hat - etwa E-Mails oder Word-Dokumente -, um damit auf der Festplatte gespeicherte Informationen wiederzufinden. Möglicherweise wird Microsoft diese Suchfunktion auch auf Webseiten ausdehnen. Außerdem sollen Anwender auf dem Bildschirm gezeigte Textinhalte leichter in Suchanfragen umsetzen können." ...
- Date
- 31.12.1996 19:29:41
22. 1.2006 18:34:49
-
Koch, T.: Searching the Web : systematic overview over indexes (1995)
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- Pages
- S.29-61
- Source
- Wissen in elektronischen Netzwerken: Strukturierung, Erschließung und Retrieval von Informationsressourcen im Internet. Eine Auswahl von Vorträgen der 19. Jahrestagung der Gesellschaft für Klassifikation, Basel 1995. Hrsg.: H.-C. Hobohm u. H.-J. Wätjen
-
Peereboom, M.: DutchESS : Dutch Electronic Subject Service - a Dutch national collaborative effort (2000)
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- Abstract
- This article gives an overview of the design and organisation of DutchESS, a Dutch information subject gateway created as a national collaborative effort of the National Library and a number of academic libraries. The combined centralised and distributed model of DutchESS is discussed, as well as its selection policy, its metadata format, classification scheme and retrieval options. Also some options for future collaboration on an international level are explored
- Date
- 22. 6.2002 19:39:23
- Theme
- Klassifikationssysteme im Online-Retrieval
-
Chaudiron, S.; Ihadjadene, M.: Studying Web search engines from a user perspective : key concepts and main approaches (2012)
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- Abstract
- This chapter shows that the wider use of Web search engines, reconsidering the theoretical and methodological frameworks to grasp new information practices. Beginning with an overview of the recent challenges implied by the dynamic nature of the Web, this chapter then traces the information behavior related concepts in order to present the different approaches from the user perspective. The authors pay special attention to the concept of "information practice" and other related concepts such as "use", "activity", and "behavior" largely used in the literature but not always strictly defined. The authors provide an overview of user-oriented studies that are meaningful to understand the different contexts of use of electronic information access systems, focusing on five approaches: the system-oriented approaches, the theories of information seeking, the cognitive and psychological approaches, the management science approaches, and the marketing approaches. Future directions of work are then shaped, including social searching and the ethical, cultural, and political dimensions of Web search engines. The authors conclude considering the importance of Critical theory to better understand the role of Web Search engines in our modern society.
- Date
- 20. 4.2012 13:22:37
- Source
- Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
-
Mooney, G.; John, R.: Intelligent information retrieval from the World Wide Web using fuzzy user modelling (1997)
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- Abstract
- Investigates the application of fuzzy logic and user modelling to information retrieval (IR) from the WWW. To overcome existing problems IR systems must become 'intelligent'. User modelling is employed in the form of user stereotypes represented as adaptive fuzzy sets. This novel approach is applied to query formulation. The results of using this approach in a prototype system are reported. In the system a query is refined before it is submitted to an existing WWW search engine. Results from a user study show that the prototype system improves upon the performance of the search engine alone
