Search (78 results, page 1 of 4)

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Abstract

Purpose - This paper aims to discuss and test the claim that user-based tagging allows for access to a wider variety of viewpoints than is found using other forms of online searching. Design/methodology/approach - A general overview of the nature of weblogs and user-based tagging is given, along with other relevant concepts. A case is then analyzed where viewpoints towards a specific issue are searched for using both tag searching (Technorati) and general search engine searching (Google and Google Blog Search). Findings - The claim to greater accessibility through user-based tagging is not overtly supported with these experiments. Further results for both general and tag-specific searching goes against some common assumptions about the types of content found on weblogs as opposed to more general web sites. Research limitations/implications - User-based tagging is still not widespread enough to give conclusive data for analysis. As this changes, further research in this area, using a variety of search subjects, is warranted. Originality/value - Although proponents of user-based tagging attribute many qualities to the practice, these qualities have not been properly documented or demonstrated. This paper partially rectifies this gap by testing one of the claims made, that of accessibility to alternate views, thus adding to the discussion on tagging for both researchers and other interested parties.

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Abstract

More and more users index everything on their own in the web 2.0. There are services for links, videos, pictures, books, encyclopaedic articles and scientific articles. All these services are library independent. But must that really be? Can't libraries help with their experience and tools to make user indexing better? On the experience of a project from German language Wikipedia together with the German person authority files (Personen Namen Datei - PND) located at German National Library (Deutsche Nationalbibliothek) I would like to show what is possible. How users can and will use the authority files, if we let them. We will take a look how the project worked and what we can learn for future projects. Conclusions - Authority files can have a role in the web 2.0 - there must be an open interface/ service for retrieval - everything that is indexed on the net with authority files can be easy integrated in a federated search - O'Reilly: You have to found ways that your data get more important that more it will be used

Content

Vortrag anlässlich des Workshops: "Extending the multilingual capacity of The European Library in the EDL project Stockholm, Swedish National Library, 22-23 November 2007".

Object

Web 2.0

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Abstract

For a long while, the creation of Web content required at least basic knowledge of Web technologies, meaning that for many Web users, the Web was de facto a read-only medium. This changed with the arrival of the "social Web," when Web applications started to allow users to publish Web content without technological expertise. Here, content creation is often an inclusive, iterative, and interactive process. Examples of social Web applications include blogs, social networking sites, as well as many specialized applications, for example, for saving and sharing bookmarks and publishing photos. Social semantic Web applications are social Web applications in which knowledge is expressed not only in the form of text and multimedia but also through informal to formal annotations that describe, reflect, and enhance the content. These annotations often take the shape of RDF graphs backed by ontologies, but less formal annotations such as free-form tags or tags from a controlled vocabulary may also be available. Wikis are one example of social Web applications for collecting and sharing knowledge. They allow users to easily create and edit documents, so-called wiki pages, using a Web browser. The pages in a wiki are often heavily interlinked, which makes it easy to find related information and browse the content.

Source

Semantic search over the Web. Eds.: R. De Virgilio, et al

Theme

Semantic Web

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Abstract

As the web has grown into an integral part of daily life, social annotation has become a popular manner for web users to manage resources. This method of management has many potential applications, but it is limited in applicability by the cold-start problem, especially for new resources on the web. In this article, we study automatic tag prediction for web pages comprehensively and utilize the predicted tags to improve search performance. First, we explore the stabilizing phenomenon of tag usage in a social bookmarking system. Then, we propose a two-stage tag prediction approach, which is efficient and is effective in making use of early annotations from users. In the first stage, content-based ranking, candidate tags are selected and ranked to generate an initial tag list. In the second stage, random-walk re-ranking, we adopt a random-walk model that utilizes tag co-occurrence information to re-rank the initial list. The experimental results show that our algorithm effectively proposes appropriate tags for target web pages. In addition, we present a framework to incorporate tag prediction in a general web search. The experimental results of the web search validate the hypothesis that the proposed framework significantly enhances the typical retrieval model.

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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

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

Tags associated with social images are valuable information source for superior image search and retrieval experiences. Although various heuristics are valuable to boost tag-based search for images, there is a lack of general framework to study the impact of these heuristics. Specifically, the task of ranking images matching a given tag query based on their associated tags in descending order of relevance has not been well studied. In this article, we take the first step to propose a generic, flexible, and extensible framework for this task and exploit it for a systematic and comprehensive empirical evaluation of various methods for ranking images. To this end, we identified five orthogonal dimensions to quantify the matching score between a tagged image and a tag query. These five dimensions are: (i) tag relatedness to measure the degree of effectiveness of a tag describing the tagged image; (ii) tag discrimination to quantify the degree of discrimination of a tag with respect to the entire tagged image collection; (iii) tag length normalization analogous to document length normalization in web search; (iv) tag-query matching model for the matching score computation between an image tag and a query tag; and (v) query model for tag query rewriting. For each dimension, we identify a few implementations and evaluate their impact on NUS-WIDE dataset, the largest human-annotated dataset consisting of more than 269K tagged images from Flickr. We evaluated 81 single-tag queries and 443 multi-tag queries over 288 search methods and systematically compare their performances using standard metrics including Precision at top-K, Mean Average Precision (MAP), Recall, and Normalized Discounted Cumulative Gain (NDCG).

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Abstract

Social tagging systems enable users to assign arbitrary tags to various digital resources. However, they face vague-meaning problems when users retrieve or present resources with the keyword-based tags. In order to solve these problems, this study takes advantage of Semantic Web technology and the topological characteristics of knowledge maps to develop a system that comprises a semantic tagging mechanism and triple-pattern and visual searching mechanisms. A field experiment was conducted to evaluate the effectiveness and user acceptance of these mechanisms in a knowledge sharing context. The results show that the semantic social tagging system is more effective than a keyword-based system. The visualized knowledge map helps users capture an overview of the knowledge domain, reduce cognitive effort for the search, and obtain more enjoyment. Traditional keyword tagging with a keyword search still has the advantage of ease of use and the users had higher intention to use it. This study also proposes directions for future development of semantic social tagging systems.

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Abstract

Purpose - This study aims to consider the value of user-assigned image tags by comparing the facets that are represented in image tags with those that are present in image queries to see if there is a similarity in the way that users describe and search for images. Design/methodology/approach - A sample dataset was created by downloading a selection of images and associated tags from Flickr, the online photo-sharing web site. The tags were categorised using image facets from Shatford's matrix, which has been widely used in previous research into image indexing and retrieval. The facets present in the image tags were then compared with the results of previous research into image queries. Findings - The results reveal that there are broad similarities between the facets present in image tags and queries, with people and objects being the most common facet, followed by location. However, the results also show that there are differences in the level of specificity between tags and queries, with image tags containing more generic terms and image queries consisting of more specific terms. The study concludes that users do describe and search for images using similar image facets, but that measures to close the gap between specific queries and generic tags would improve the value of user tags in indexing image collections. Originality/value - Research into tagging has tended to focus on textual resources with less research into non-textual documents. In particular, little research has been undertaken into how user tags compare to the terms used in search queries, particularly in the context of digital images.

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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.
A number of such utilities are presented here, together with an emergent new class of tools that caters more to the academic communities and that stores not only user-supplied tags, but also structured citation metadata terms wherever it is possible to glean this information from service providers. This provision of rich, structured metadata means that the user is provided with an accurate third-party identification of a document, which could be used to retrieve that document, but is also free to search on user-supplied terms so that documents of interest (or rather, references to documents) can be made discoverable and aggregated with other similar descriptions either recorded by the user or by other users. Matt Biddulph in an XML.com article last year, in which he reviews one of the better known social bookmarking tools, del.icio.us, declares that the "del.icio.us-space has three major axes: users, tags, and URLs". We fully support that assessment but choose to present this deconstruction in a reverse order. This paper thus first recaps a brief history of bookmarks, then discusses the current interest in tagging, moves on to look at certain social issues, and finally considers some of the feature sets offered by the new bookmarking tools. A general review of a number of common social bookmarking tools is presented in the annex. A companion paper describes a case study in more detail: the tool that Nature Publishing Group has made available to the scientific community as an experimental entrée into this field - Connotea; our reasons for endeavouring to provide such a utility; and experiences gained and lessons learned.

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Abstract

Social media systems have encouraged end user participation in the Internet, for the purpose of storing and distributing Internet content, sharing opinions and maintaining relationships. Collaborative tagging allows users to annotate the resulting user-generated content, and enables effective retrieval of otherwise uncategorised data. However, compared to professional web content production, collaborative tagging systems face the challenge that end-users assign tags in an uncontrolled manner, resulting in unsystematic and inconsistent metadata. This paper introduces a framework for the personalization of social media systems. We pinpoint three tasks that would benefit from personalization: collaborative tagging, collaborative browsing and collaborative search. We propose a ranking model for each task that integrates the individual user's tagging history in the recommendation of tags and content, to align its suggestions to the individual user preferences. We demonstrate on two real data sets that for all three tasks, the personalized ranking should take into account both the user's own preference and the opinion of others.

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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

Folksonomy is the result of describing Web resources with tags created by Web users. Although it has become a popular application for the description of resources, in general terms Folksonomies are not being conveniently integrated in metadata. However, if the appropriate metadata elements are identified, then further work may be conducted to automatically assign tags to these elements (RDF properties) and use them in Semantic Web applications. This article presents research carried out to continue the project Kinds of Tags, which intends to identify elements required for metadata originating from folksonomies and to propose an application profile for DC Social Tagging. The work provides information that may be used by software applications to assign tags to metadata elements and, therefore, means for tags to be conveniently gathered by metadata interoperability tools. Despite the unquestionably high value of DC and the significance of the already existing properties in DC Terms, the pilot study show revealed a significant number of tags for which no corresponding properties yet existed. A need for new properties, such as Action, Depth, Rate, and Utility was determined. Those potential new properties will have to be validated in a later stage by the DC Social Tagging Community.

Pages

S.14-22

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Abstract

Libraries are the tools we use to learn and to answer our questions. The quality of our work depends, among others, on the quality of the tools we use. Recent research in digital libraries is focused, on one hand on improving the infrastructure of the digital library management systems (DLMS), and on the other on improving the metadata models used to annotate collections of objects maintained by DLMS. The latter includes, among others, the semantic web and social networking technologies. Recently, the semantic web and social networking technologies are being introduced to the digital libraries domain. The expected outcome is that the overall quality of information discovery in digital libraries can be improved by employing social and semantic technologies. In this chapter we present the results of an evaluation of social and semantic end-user information discovery services for the digital libraries.

Date

1. 8.2010 12:35:22

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Abstract

The growing predominance of social semantics in the form of tagging presents the metadata community with both opportunities and challenges as for leveraging this new form of information content representation and for retrieval. One key challenge is the absence of contextual information associated with these tags. This paper presents an experiment working with Flickr tags as an example of utilizing social semantics sources for enriching subject metadata. The procedure included four steps: 1) Collecting a sample of Flickr tags, 2) Calculating cooccurrences between tags through mutual information, 3) Tracing contextual information of tag pairs via Google search results, 4) Applying natural language processing and machine learning techniques to extract semantic relations between tags. The experiment helped us to build a context sentence collection from the Google search results, which was then processed by natural language processing and machine learning algorithms. This new approach achieved a reasonably good rate of accuracy in assigning semantic relations to tag pairs. This paper also explores the implications of this approach for using social semantics to enrich subject metadata.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Abstract

Some members of the library community, including the Library of Congress Working Group on the Future of Bibliographic Control, have suggested that libraries should open up their catalogs to allow users to add descriptive tags to the bibliographic data in catalog records. The web site LibraryThing currently permits its members to add such user tags to its records for books and therefore provides a useful resource to contrast with library bibliographic records. A comparison between the LibraryThing tags for a group of books and the library-supplied subject headings for the same books shows that users and catalogers approach these descriptors very differently. Because of these differences, user tags can enhance subject access to library materials, but they cannot entirely replace controlled vocabularies such as the Library of Congress subject headings.

Date

10. 9.2000 17:38:22

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Abstract

The goal of the study presented in this article is to investigate to what extent the classification of a web page by a single genre matches the users' perspective. The extent of agreement on a single genre label for a web page can help understand whether there is a need for a different classification scheme that overrides the single-genre labelling. My hypothesis is that a single genre label does not account for the users' perspective. In order to test this hypothesis, I submitted a restricted number of web pages (25 web pages) to a large number of web users (135 subjects) asking them to assign only a single genre label to each of the web pages. Users could choose from a list of 21 genre labels, or select one of the two 'escape' options, i.e. 'Add a label' and 'I don't know'. The rationale was to observe the level of agreement on a single genre label per web page, and draw some conclusions about the appropriateness of limiting the assignment to only a single label when doing genre classification of web pages. Results show that users largely disagree on the label to be assigned to a web page.

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Content

The Web of User Contribution - Foundations and Principles of the Social Web - Social Tagging - Rating and Filtering of Digital Resources Empirical Analysisof User Contributions - The Functional and Linguistic Structure of Tags - A Comparative Analysis of Tags for Different Digital Resource Types - Exploring Relevance Assessments in Social IR Systems - Exploring User Contribution Within a Higher Education Scenario - Summary of Empirical Results and Implications for Designing Social Information Systems User Contribution for a Participative Information System - Social Information Architecture for an Online Help System

Object

Web 2.0

RSWK

World Wide Web 2.0 / Benutzer / Online-Publizieren / Information Retrieval / Soziale Software / Hilfesystem
Social Tagging / Filter / Web log / World Wide Web 2.0

Subject

World Wide Web 2.0 / Benutzer / Online-Publizieren / Information Retrieval / Soziale Software / Hilfesystem
Social Tagging / Filter / Web log / World Wide Web 2.0

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Abstract

A new collaborative approach in information organization and sharing has recently arisen, known as collaborative tagging or social indexing. A key element of collaborative tagging is the concept of collective intelligence (CI), which is a shared intelligence among all participants. This research investigates the phenomenon of social tagging in the context of CI with the aim to serve as a stepping-stone towards the mining of truly valuable social tags for web resources. This study focuses on assessing and evaluating the degree of CI embedded in social tagging over time in terms of two-parameter values, number of participants, and top frequency ranking window. Five different metrics were adopted and utilized for assessing the similarity between ranking lists: overlapList, overlapRank, Footrule, Fagin's measure, and the Inverse Rank measure. The result of this study demonstrates that a substantial degree of CI is most likely to be achieved when somewhere between the first 200 and 400 people have participated in tagging, and that a target degree of CI can be projected by controlling the two factors along with the selection of a similarity metric. The study also tests some experimental conditions for detecting social tags with high CI degree. The results of this study can be applicable to the study of filtering social tags based on CI; filtered social tags may be utilized for the metadata creation of tagged resources and possibly for the retrieval of tagged resources.

Date

25.12.2012 15:22:37

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Abstract

In diesem Kapitel wird die zentrale Bedeutung der Annotation von Webdokumenten bzw. von Ressourcen in einem Semantischen Web diskutiert. Es wird auf aktuelle Methoden und Techniken in diesem Gebiet eingegangen, insbesondere wird das Phänomen "Social Tagging" als zentrales Element eines "Social Semantic Webs" beleuchtet. Weiters wird der Frage nachgegangen, welchen Mehrwert "Tag Recommender" beim Annotationsvorgang bieten, sowohl aus Sicht des End-Users aber auch im Sinne eines kollaborativen Ontologieerstellungsprozesses. Schließlich wird ein Funktionsprinzip für einen semi-automatischen Tag-Recommender vorgestellt unter besonderer Berücksichtigung der Anwendbarkeit in einem Corporate Semantic Web.

Source

Social Semantic Web: Web 2.0, was nun? Hrsg.: A. Blumauer u. T. Pellegrini