Search (73 results, page 2 of 4)

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Abstract

Mit sozialen Suchdiensten - wie z. B. Yahoo Clever, Lycos iQ oder Mister Wong - ist eine Ergänzung und teilweise sogar eine Konkurrenz zu den bisherigen Ansätzen in der Web-Suche entstanden. Während Google und Co. automatisch generierte Trefferlisten bieten, binden soziale Suchdienste die Anwender zu Generierung der Suchergebnisse in den Suchprozess ein. Vor diesem Hintergrund wird in diesem Buch der Frage nachgegangen, inwieweit soziale Suchdienste mit traditionellen Suchmaschinen konkurrieren oder diese qualitativ ergänzen können. Der vorliegende Band beleuchtet die hier aufgeworfene Fragestellung aus verschiedenen Perspektiven, um auf die Bedeutung von sozialen Suchdiensten zu schließen.

Issue

Ergebnisse des Fachprojektes "Einbindung von Frage-Antwort-Diensten in die Web-Suche" am Department Information der Hochschule für Angewandte Wissenschaften Hamburg (WS 2007/2008).

RSWK

World Wide Web 2.0 / Suchmaschine

Subject

World Wide Web 2.0 / Suchmaschine

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Abstract

With the emergence of Web 2.0, sharing personal content, communicating ideas, and interacting with other online users in Web 2.0 communities have become daily routines for online users. User-generated data from Web 2.0 sites provide rich personal information (e.g., personal preferences and interests) and can be utilized to obtain insight about cyber communities and their social networks. Many studies have focused on leveraging user-generated information to analyze blogs and forums, but few studies have applied this approach to video-sharing Web sites. In this study, we propose a text-based framework for video content classification of online-video sharing Web sites. Different types of user-generated data (e.g., titles, descriptions, and comments) were used as proxies for online videos, and three types of text features (lexical, syntactic, and content-specific features) were extracted. Three feature-based classification techniques (C4.5, Naïve Bayes, and Support Vector Machine) were used to classify videos. To evaluate the proposed framework, user-generated data from candidate videos, which were identified by searching user-given keywords on YouTube, were first collected. Then, a subset of the collected data was randomly selected and manually tagged by users as our experiment data. The experimental results showed that the proposed approach was able to classify online videos based on users' interests with accuracy rates up to 87.2%, and all three types of text features contributed to discriminating videos. Support Vector Machine outperformed C4.5 and Naïve Bayes techniques in our experiments. In addition, our case study further demonstrated that accurate video-classification results are very useful for identifying implicit cyber communities on video-sharing Web sites.

Object

Web 2.0

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Abstract

There are close to a billion websites on the Internet with approximately 400 million users worldwide [www.internetworldstats.com]. People go to websites for a wide variety of different information tasks, from finding a restaurant to serious research. Many of the difficulties with searching the Web, as it is structured currently, can be attributed to increases to scale. The content of the Web is now so large that we only have a rough estimate of the number of sites and the range of information is extremely diverse, from blogs and photos to research articles and news videos.

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Abstract

Die Erforschung und der Einsatz von Folksonomies und Social Tagging als nutzerzentrierte Formen der Inhaltserschließung und Wissensrepräsentation haben in den 10 Jahren ab ca. 2005 ihren Höhenpunkt erfahren. Motiviert wurde dies durch die Entwicklung und Verbreitung des Social Web und der wachsenden Nutzung von Social-Media-Plattformen (s. Kapitel E 8 Social Media und Social Web). Beides führte zu einem rasanten Anstieg der im oder über das World Wide Web auffindbaren Menge an potenzieller Information und generierte eine große Nachfrage nach skalierbaren Methoden der Inhaltserschließung.

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Abstract

Social tagging is one of the major phenomena transforming the World Wide Web from a static platform into an actively shared information space. This paper addresses various aspects of social tagging, including different views on the nature of social tagging, how to make use of social tags, and how to bridge social tagging with other Web functionalities; it discusses the use of facets to facilitate browsing and searching of tagging data; and it presents an analogy between bibliometrics and tagometrics, arguing that established bibliometric methodologies can be applied to analyze tagging behavior on the Web. Based on the Upper Tag Ontology (UTO), a Web crawler was built to harvest tag data from Delicious, Flickr, and YouTube in September 2007. In total, 1.8 million objects, including bookmarks, photos, and videos, 3.1 million taggers, and 12.1 million tags were collected and analyzed. Some tagging patterns and variations are identified and discussed.

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Abstract

Social bookmarking has gained popularity since the advent of Web 2.0. Keywords known as tags are created to annotate web content, and the resulting tag space composed of the tags, the resources, and the users arises as a new platform for web content discovery. Useful and interesting web resources can be located through searching and browsing based on tags, as well as following the user-user connections formed in the social bookmarking community. However, the effectiveness of tag-based search is limited due to the lack of explicitly represented semantics in the tag space. In addition, social connections between users are underused for web content discovery because of the inadequate social functions. In this research, we propose a comprehensive framework to reorganize the flat tag space into a hierarchical faceted model. We also studied the structure and properties of various networks emerging from the tag space for the purpose of more efficient web content discovery. The major research approach used in this research is social network analysis (SNA), together with methodologies employed in design science research. The contribution of our research includes: (i) a faceted model to categorize social bookmarking tags; (ii) a relationship ontology to represent the semantics of relationships between tags; (iii) heuristics to reorganize the flat tag space into a hierarchical faceted model using analysis of tag-tag co-occurrence networks; (iv) an implemented prototype system as proof-of-concept to validate the feasibility of the reorganization approach; (v) a set of evaluations of the social functions of the current networking features of social bookmarking and a series of recommendations as to how to improve the social functions to facilitate web content discovery.

Content

A Dissertation Submitted to the Faculty of the COMMITTEE ON BUSINESS ADMINISTRATION In Partial Fulfillment of the Requirements For the Degree of DOCTOR OF PHILOSOPHY WITH A MAJOR IN MANAGEMENT In the Graduate College THE UNIVERSITY OF ARIZONA. Vgl.: http://hdl.handle.net/10150/195123. Vgl. auch: https://www.semanticscholar.org/paper/Utilizing-social-bookmarking-tag-space-for-web-a-Ram-Wei/da9e7e5ee771008b741af7176d3f0d67128d1dca.

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Abstract

Folksonomies ermöglichen den Nutzern in Kollaborativen Informationsdiensten den Zugang zu verschiedenartigen Informationsressourcen. In welchen Fällen beide Bestandteile des Web 2.0 am besten für das Information Retrieval geeignet sind und wo sie die Websuche ggf. ersetzen können, wird in diesem Beitrag diskutiert. Dazu erfolgt eine detaillierte Betrachtung der Reichweite von Social-Bookmarking-Systemen und Sharing-Systemen sowie der Retrievaleffektivität von Folksonomies innerhalb von Kollaborativen Informationsdiensten.

Source

Handbuch Internet-Suchmaschinen, 2: Neue Entwicklungen in der Web-Suche. Hrsg.: D. Lewandowski

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Abstract

Nach dem zu Beginn der Ära des World Wide Web von Hand gepflegte Linklisten und -Verzeichnisse und an Freunde und Kollegen per E-Mail verschickte Links genügten, um die Informationen zu finden, nach denen man suchte, waren schon bald Volltextsuchmaschinen und halbautomatisch betriebene Kataloge notwendig, um den mehr und mehr anschwellenden Informationsfluten des Web Herr zu werden. Heute bereits sind diese Dämme gebrochen und viele Millionen Websites halten Billionen an Einzelseiten mit Informationen vor, von Datenbanken und anderweitig versteckten Informationen ganz zu schweigen. Mit Volltextsuchmaschinen erreicht man bei dieser Masse keine befriedigenden Ergebnisse mehr. Entweder man erzeugt lange Suchterme mit vielen Ausschließungen und ebenso vielen nicht-exklusiven ODER-Verknüpfungen um verschiedene Schreibweisen für den gleichen Term abzudecken oder man wählt von vornherein die Daten-Quelle, an die man seine Fragen stellt, genau aus. Doch oft bleiben nur klassische Web-Suchmaschinen übrig, zumal wenn der Fragende kein Informationsspezialist mit Kenntnissen von Spezialdatenbanken ist, sondern, von dieser Warte aus gesehenen, ein Laie. Und nicht nur im Web selbst, auch in unternehmensinternen Intranets steht man vor diesem Problem. Tausende von indizierten Dokumente mögen ein Eckdatum sein, nach dem sich der Erfolg der Einführung eines Intranets bemessen lässt, aber eine Aussage über die Nützlichkeit ist damit nicht getroffen. Und die bleibt meist hinter den Erwartungen zurück, vor allem bei denen Mitarbeitern, die tatsächlich mit dem Intranet arbeiten müssen. Entscheidend ist für die Informationsauffindung in Inter- und Intranet eine einfach zu nutzende und leicht anpassbare Möglichkeit, neue interessante Inhalte zu entdecken. Mit Tags steht eine mögliche Lösung bereit.

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Abstract

Data integration and mediation have become central concerns of information technology over the past few decades. With the advent of the Web and the rapid increases in the amount of data and the number of Web documents and users, researchers have focused on enhancing the interoperability of data through the development of metadata schemes. Other researchers have looked to the wealth of metadata generated by bookmarking sites on the Social Web. While several existing ontologies have capitalized on the semantics of metadata created by tagging activities, the Upper Tag Ontology (UTO) emphasizes the structure of tagging activities to facilitate modeling of tagging data and the integration of data from different bookmarking sites as well as the alignment of tagging ontologies. UTO is described and its utility in modeling, harvesting, integrating, searching, and analyzing data is demonstrated with metadata harvested from three major social tagging systems (Delicious, Flickr, and YouTube).

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Abstract

Because, to paraphrase a pop music lyric from a certain rock and roll band of yesterday, "the Web is old, the Web is new, the Web is all, the Web is you", it seems like we might have to face up to some of these stark realities. With the introduction of new social software applications such as blogs, wikis, newsfeeds, social networks, and bookmarking tools (the subject of this paper), the claim that Shelley Powers makes in a Burningbird blog entry seems apposite: "This is the user's web now, which means it's my web and I can make the rules." Reinvention is revolution - it brings us always back to beginnings. We are here going to remind you of hyperlinks in all their glory, sell you on the idea of bookmarking hyperlinks, point you at other folks who are doing the same, and tell you why this is a good thing. Just as long as those hyperlinks (or let's call them plain old links) are managed, tagged, commented upon, and published onto the Web, they represent a user's own personal library placed on public record, which - when aggregated with other personal libraries - allows for rich, social networking opportunities. Why spill any ink (digital or not) in rewriting what someone else has already written about instead of just pointing at the original story and adding the merest of titles, descriptions and tags for future reference? More importantly, why not make these personal 'link playlists' available to oneself and to others from whatever browser or computer one happens to be using at the time? This paper reviews some current initiatives, as of early 2005, in providing public link management applications on the Web - utilities that are often referred to under the general moniker of 'social bookmarking tools'. There are a couple of things going on here: 1) server-side software aimed specifically at managing links with, crucially, a strong, social networking flavour, and 2) an unabashedly open and unstructured approach to tagging, or user classification, of those links.

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Pages

S.15-22

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RSWK

Bibliothek / Web log

Subject

Bibliothek / Web log

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Abstract

Large image collections on the Web need to be organized for effective retrieval. Metadata has a key role in image retrieval but rely on professionally assigned tags which is not a viable option. Current content-based image retrieval systems have not demonstrated sufficient utility on large-scale image sources on the web, and are usually used as a supplement to existing text-based image retrieval systems. We present two social tagging alternatives in the form of photo-sharing networks and image labeling games. Here we analyze these applications to evaluate their usefulness from the semantic point of view, investigating the management of social tagging for indexing. The findings of the study have shown that social tagging can generate a sizeable number of tags that can be classified as in terpretive for an image, and that tagging behaviour has a manageable and adjustable nature depending on tagging guidelines.

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Date

21. 6.2009 12:22:44

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Abstract

Open Rating Systeme werden zur Be­wertung unterschiedlichster Objekte eingesetzt. Benutzer können Rezensionen über Objekte verfassen, andere Benutzer können die Qualität dieser Rezensionen bewerten. Basierend auf diesen Bewertungen der Rezensionen wird ein Vertrauensnetzwerk (Web of Trust) aufgebaut. Zwei Benutzer werden durch eine gerichtete Kante verbunden, wenn ein Benutzer dem System mitteilt, dass er einem anderen Benutzer vertraut, Inhalte korrekt zu bewerten. Basierend auf diesem persönlichen Vertrauensnetzwerk werden Objekte und auch die Rezensionen für ein bestimmtes Objekt individuell für jeden Benutzer angeordnet.

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Abstract

Autoren wissenschaftlicher Artikel stehen unterschiedliche Wege bei der Recherche nach Hintergrundmaterial zu ihren Projekten zur Verfügung. Dass Social-Bookmarking-Dienste, die als Teil des Web 2.0 (O'Reilly, 2005) und der Bibliothek 2.0 (Danowski, 2006) genannt werden, eine sinnvolle Ergänzung zu den herkömmlichen Nachweisdatenbanken sein können, soll der vorliegende Artikel zeigen.

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Abstract

Today I want to talk about categorization, and I want to convince you that a lot of what we think we know about categorization is wrong. In particular, I want to convince you that many of the ways we're attempting to apply categorization to the electronic world are actually a bad fit, because we've adopted habits of mind that are left over from earlier strategies. I also want to convince you that what we're seeing when we see the Web is actually a radical break with previous categorization strategies, rather than an extension of them. The second part of the talk is more speculative, because it is often the case that old systems get broken before people know what's going to take their place. (Anyone watching the music industry can see this at work today.) That's what I think is happening with categorization. What I think is coming instead are much more organic ways of organizing information than our current categorization schemes allow, based on two units -- the link, which can point to anything, and the tag, which is a way of attaching labels to links. The strategy of tagging -- free-form labeling, without regard to categorical constraints -- seems like a recipe for disaster, but as the Web has shown us, you can extract a surprising amount of value from big messy data sets.

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Abstract

Today, in times of Web 2.0., graduates and undergraduates interact in virtual communities like studiVZ (Studentenverzeichnis) and generate content by reviewing or tagging documents. This phenomenon offers good prospects for academic libraries. They can use the customers' tags for indexing the growing amount of electronic resources and thereby optimize the search for these documents. Important examples are the journals, databases and e-books included in the "Nationallizenzen" financed by the German Research Foundation (DFG). The documents in this collection are not manually indexed by librarians and have no annotation according to the German standard classification systems. Connecting search systems by means of Web-2.0.-services is an important task for libraries. For this purpose users are encouraged to tag printed and electronic resources in search systems like the libraries' online catalogs and to establish connections between entries in other systems, e.g. Bibsonomy, and the items found in the online catalog. As a consequence annotations chosen by both, users and librarians, will coexist: The items in the tagging systems and the online catalog are linked, library users may find other publications of interest, and contacts between library users with similar scientific interests may be established. Librarians have to face the fact that user generated tags do not necessarily have the same quality as their own annotations and will therefore have to seek for instruments for comparing user generated tags with library generated keywords.

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Abstract

Web 2.0 and social/collaborative tagging have altered the traditional roles of indexer and user. Traditional indexing tools and systems assume the top-down approach to indexing in which a trained professional is responsible for assigning index terms to information sources with a potential user in mind. However, in today's Web, end users create, organize, index, and search for images and other information sources through social tagging and other collaborative activities. One of the impediments to user-centered indexing had been the cost of soliciting user-generated index terms or tags. Social tagging of images such as those on Flickr, an online photo management and sharing application, presents an opportunity that can be seized by designers of indexing tools and systems to bridge the semantic gap between indexer terms and user vocabularies. Empirical research on the differences and similarities between user-generated tags and index terms based on controlled vocabularies has the potential to inform future design of image indexing tools and systems. Toward this end, a random sample of Flickr images and the tags assigned to them were content analyzed and compared with another sample of index terms from a general image collection using established frameworks for image attributes and contents. The results show that there is a fundamental difference between the types of tags and types of index terms used. In light of this, implications for research into and design of user-centered image indexing tools and systems are discussed.

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Abstract

This study employs the FRBR (Functional Requirements for Bibliographic Records) conceptual model to provide in-depth investigation on the characteristics of social tags by analyzing the bibliographic attributes of tags that are not limited to subject properties. FRBR describes four different levels of entities (i.e., Work, Expression, Manifestation, and Item), which provide a distinguishing understanding of each entity in the bibliographic universe. In this research, since the scope of data analysis focuses on tags assigned to web documents, consideration on Manifestation and Item has been excluded. Accordingly, only the attributes of Work and Expression entity were investigated in order to map the attributes of tags to attributes defined in those entities. The content analysis on tag attributes was conducted on a total of 113 web documents regarding 11 attribute categories defined by FRBR. The findings identified essential bibliographic attributes of tags and tagging behaviors by subject. The findings showed that concerning specific subject areas, taggers exhibited different tagging behaviors representing distinctive features and tendencies. These results have led to the conclusion that there should be an increased awareness of diverse user needs by subject in terms of the practical implications of metadata generation.