Search (21 results, page 1 of 2)

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Abstract

What is the role of controlled vocabulary in a Web 2.0 world? Can we have the best of both worlds: balancing folksonomies and controlled vocabularies to help communities of users find and share information and resources most relevant to them? education.au develops and manages Australian online services for education and training. Its goal is to bring people, learning and technology together. education.au projects are increasingly involved in exploring the use of Web 2.0 developments building on user ideas, knowledge and experience, and how these might be integrated with existing information management systems. This paper presents work being undertaken in this area, particularly in relation to controlled vocabularies, and discusses the challenges faced. Education Network Australia (edna) is a leading online resource collection and collaborative network for education, with an extensive repository of selected educational resources with metadata created by educators and information specialists. It uses controlled vocabularies for metadata creation and searching, where users receive suggested related terms from an education thesaurus, with their results. We recognise that no formal thesaurus can keep pace with user needs so are interested in exploiting the power of folksonomies. We describe a proof of concept project to develop community contributions to managing information and resources, using Taxonomy-Directed Folksonomy. An established taxonomy from the Australian education sector suggests terms for tagging and users can suggest terms. Importantly, the folksonomy will feed back into the taxonomy showing gaps in coverage and helping us to monitor new terms and usage to improve and develop our formal taxonomies. This model would initially sit alongside the current edna repositories, tools and services but will give us valuable user contributed resources as well as information about how users manage resources. Observing terms suggested, chosen and used in folksonomies is a rich source of information for developing our formal systems so that we can indeed get the best of both worlds.

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Abstract

Services in Web 2.0 generate a large quantity of information, distributed over a range of resources (e.g. photos, URLs, videos) and integrated into different platforms (e.g. social bookmarking systems, sharing platforms (Peters, 2009). To adequately use this mass of information and to extract it from the platforms, users must be equipped with suitable tools and knowledge. After all, the best information is useless if users cannot find it: 'The model of information consumption relies on the information being found' (Vander Wal, 2004). In Web 2.0, the retrieval component has been established through so-called folksonomies (Vander Wal, 2005a), which are considered as several combinations of an information resource, one or more freely chosen keywords ('tags') and a user. Web 2.0 services that use folksonomies as an indexing and retrieval tool are defined as 'collaborative information services' because they allow for the collaborative creation of a public database that is accessible to all users (registered, where necessary) via the tags of the folksonomy (Ding et al., 2009; Heymann, Paepcke and Garcia-Molina, 2010).

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Abstract

The essence of folksonomies is user-created descriptive metadata as opposed to the traditional sender-determined descriptive metadata in taxonomies and faceted classification. We briefly introduce the beginning and principles of folksonomy and discuss the categorizing concept of folksonomies on the basis of the computer program del.icio.us. The selection of the metadata tagged is not accidental, rather tagging follows a pattern that proves to be the pattern for the classic power law, which, in many complex systems is seen to unfold as an imitation-dynamic that creates an asymmetry, where a few descriptive metadata are often reproduced and the majority seldom reproduced. In del.icio.us, it is the very broad and basic subject headings that are often reproduced and achieve power in the system - which in cognitive psychology is called cognitive basic categories - while the small, more specific subject headings are seldom reproduced. The law of power's underlying imitation-dynamic in del.icio.us is explained from the perspective of different theoretical paradigms, i.e. network, economy and cognition. The theorectical and speculative conclusion is that the law of power and asymmetry is biased by a cognitive economizing through a simplification principle in the users construction of descriptive metadata. Free tagging in folksonomies is comparable to empirical experiments in free categorization. Users often choose broad basic categories, because that requires the least cognitive effort. The consequences are that folksonomy is not necessarily a better, more realistic and cheaper method of creating metadata than that which can be generated through taxonomies, faceted classification or search algorithms. Folksonomy as a self-organizing system likely cannot create better and cheaper descriptive metadata.

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Abstract

Folksonomies are indexing languages that emerge from the distributed resource-description activity of multiple agents who make use of online tagging services to assign tags (i.e., category labels) to the resources in collections. Although individuals' motivations for engaging in tagging activity vary widely, folksonomy-based retrieval systems can be evaluated by measuring the degree to which taggers and searchers agree on tag-resource pairings.

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Abstract

There is a growing interest into how we represent and share tagging data in collaborative tagging systems. Conventional tags, meaning freely created tags that are not associated with a structured ontology, are not naturally suited for collaborative processes, due to linguistic and grammatical variations, as well as human typing errors. Additionally, tags reflect personal views of the world by individual users, and are not normalised for synonymy, morphology or any other mapping. Our view is that the conventional approach provides very limited semantic value for collaboration. Moreover, in cases where there is some semantic value, automatically sharing semantics via computer manipulations is extremely problematic. This paper explores these problems by discussing approaches for collaborative tagging activities at a semantic level, and presenting conceptual models for collaborative tagging activities and folksonomies. We present criteria for the comparison of existing tag ontologies and discuss their strengths and weaknesses in relation to these criteria.

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

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

Documentation of art museum collections has been traditionally written by and for art historians. To make art museum collections broadly accessible, and to enable art museums to engage their communities, means of access need to reflect the perspectives of other groups and communities. Social Tagging (the collective assignment of keywords to resources) and its resulting Folksonomy (the assemblage of concepts expressed in such a cooperatively developed system of classification) offer ways for art museums to engage with their communities and to understand what users of online museum collections see as important. Proof of Concept studies at The Metropolitan Museum of Art compared terms assigned by trained cataloguers and untrained cataloguers to existing museum documentation, and explored the potential for social tagging to improve access to museum collections. These preliminary studies, the results of which are reported here, have shown the potential of social tagging and folksonomy to open museum collections to new, more personal meanings. Untrained cataloguers identified content elements not described in formal museum documentation. Results from these tests - the first in the domain - provided validation for exploring social tagging and folksonomy as an access strategy within The Metropolitan Museum, motivation to proceed with a broader inter-institutional collaboration, and input into the development of a multi-institutional collaboration exploring tagging in art museums. Tags assigned by users might help bridge the semantic gap between the professional discourse of the curator and the popular language of the museum visitor. The steve collaboration (http://www.steve.museum) is building on these early studies to develop shared tools and research methods that enable social tagging of art museum collections and explore the utility of folksonomy for providing enhanced access to collections.

Content

Beitrag eines Themenheftes "Knowledge organization systems and services"

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Content

"Irgendwann ist es einfach zu viel Information. Einmal "Schokolade" bei Google eingeben und mal eben 9 870 000 Links zur Auswahl. "Pilgern - 800 000 Einträge. 21400 000 für "Hörbuch. Die Auswahl fällt schwer, und wer hat schon die Geduld, sich alle Seiten anzugucken. Am besten wäre es, irgendjemand könnte eine der, vielen Seiten empfehlen. Auf eben dieses Prinzip setzen immer mehr Internet-Seiten. Seiten wie www.mister-wong.de bestehen nur aus Empfehlungen von Nutzern für Nutzer. Immerhin vier empfehlen die Webseite zum Pralinenclub, acht Nutzer haben sich für www.theobroma-cacao.de ein Lesezeichen angelegt, beim Pilgern sind sich auch gleich einige Benutzer einig, welche Seite sie am liebsten zum Thema lesen und empfehlen. "Social bookmarks" - Lesezeichen, die man anderen zur Verfügung stellt - sind vor allem auf englischsprachigen Seiten zu finden. Mit Anbietern wie "Mister Wong" oder "Netselektor" können jetzt auch die Deutschen ihre Lieblingslesezeichen im Internet mit anderen teilen. "Bei den großen Suchmaschinen haben es gute Seiten oft schwer: Wenn sie nicht bei Yahoo oder Google nach der Suchanfrage ganz oben stehen, findet sie niemand", sagt "Mister Wong"Pressesprecher Christian Clawien. Für ihn ist das Konzept der "Social bookmarks" die ideale Alternative zur mechanischen Suchmaschine. Noch sind die Zahlen der Aktiven aber gering. 1,3 Millionen abgespeicherte Bookmarks verzeichnet "Mister Wong" seit der Gründung im März 2006. Vor allem Leute, die sowieso bereits einen guten Draht zum Internet haben, nutzten das Angebot, sagt Clawien. Langsam beginnt die Phase, wo Monetarisierung möglich ist." Langfristig soll auch Werbung auf der Seite erscheinen. Bei "www.netselektor.de", im November 2006 gegründet, sitzt zudem noch eine Redaktion vor dem Computer, die die abgelegten Lesezeichen der Nutzer durchforstet und die besten Empfehlungen noch mal als qualitativ hochwertig vorstellt. Nach und nach soll so in Zusammenarbeit mit den Usern ein "Best-of-Internet" entstehen. Natürlich nur mit den Internet-Juwelen, die einer Empfehlung würdig sind. Allerdings erreichen die "Social bookmark"-Seiten auch schnell ihre Grenzen: Nicht alle Stichworte bringen Ergebnisse, nicht immer sind die Vorlieben der Nutzer für Internet-Seiten nachvollziehbar, und noch reicht auch nicht die Anzahl der beteiligten Nutzer, um tatsächlich all die verborgenen Juwelen im riesigen weltweiten Netz zutage zu fördern. Originelles gibt es aber trotzdem schon jetzt - vom Karaoke Trainer bis zu www.dontclick.it", die Seite, die ohne Maus funktionieren soll."

Date

3. 5.1997 8:44:22

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Abstract

Folksonomy, a free-form tagging, is a user-generated classification system of web contents that allows users to tag their favorite web resources with their chosen words or phrases selected from natural language. These tags (also called concepts, categories, facets or entities) can be used to classify web resources and to express users' preferences. Folksonomy-based systems allow users to classify web resources through tagging bookmarks, photos or other web resources and saving them to a public web site like Del.icio.us. Thus information about web resources and online articles can be shared in an easy way. The purpose of this study is to provide an overview of the folksonomy tagging phenomenon (also called social tagging and social bookmarking) and explore some of the reasons why we need controlled vocabularies, discussing the problems associated with folksonomy.

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Abstract

The field of subject analysis enjoyed a flurry of interest in the 1970s, and has recently become a focus of attention again. The scholarly community doing work in this area has become more diffuse, and has grown to include new groups, such as information architects. Changes in information services and information seeking have led to reexamination of the nature and role of subject analysis tools and practices. This selective review looks at thesauri, guided navigation, and folksonomy as three activity areas in which subject analysis researchers have been attempting to address rapidly changing new environments.

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Abstract

Catalogers have always had to balance adherence to cataloging rules and authority files with creating cataloging that is current and relevant to users. That dilemma has been complicated in new ways because of user demands in the world of Web 2.0. Standardized cataloging is crucial for communication between computer systems, but patrons now have an expectation of social interaction on the Internet, as evidenced by the popularity of folksonomy. After a description of traditional subject cataloging and folksonomy, this article discusses several institutions where subject cataloging is still used, but where patron interaction is also encouraged. User-generated tags can coexist with controlled vocabulary such as subject headings.

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Date

22. 9.2007 15:41:14

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Abstract

Purpose - Many Web 2.0 services (including Library 2.0 catalogs) make use of folksonomies. The purpose of this paper is to cut off all tags in the long tail of a document-specific tag distribution. The remaining tags at the beginning of a tag distribution are considered power tags and form a new, additional search option in information retrieval systems. Design/methodology/approach - In a theoretical approach the paper discusses document-specific tag distributions (power law and inverse-logistic shape), the development of such distributions (Yule-Simon process and shuffling theory) and introduces search tags (besides the well-known index tags) as a possibility for generating tag distributions. Findings - Search tags are compatible with broad and narrow folksonomies and with all knowledge organization systems (e.g. classification systems and thesauri), while index tags are only applicable in broad folksonomies. Based on these findings, the paper presents a sketch of an algorithm for mining and processing power tags in information retrieval systems. Research limitations/implications - This conceptual approach is in need of empirical evaluation in a concrete retrieval system. Practical implications - Power tags are a new search option for retrieval systems to limit the amount of hits. Originality/value - The paper introduces power tags as a means for enhancing the precision of search results in information retrieval systems that apply folksonomies, e.g. catalogs in Library 2.0environments.

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Abstract

The subject of this article is folksonomies on the Internet. One of the largest folksonomies on the Internet in terms of number of users and tagged websites is the computer program del.icio.us, where more than 100,000 people have tagged the websites that they and others find using their own keywords. How this is done in practice and the patterns to be found are the focus of this article. The empirical basis is the collection of 76,601 different keywords with a total frequency of 178,215 from 500 randomly chosen taggers on del.icio.us at the end of 2005. The keywords collected were then analyzed quantitatively statistically by uncovering their frequency and percentage distribution and through a statistical correspondence analysis in order to uncover possible patterns in the users' tags. Subsequently, a qualitative textual analysis of the tags was made in order to find out by analysis which tagging strategies are represented in the data material. This led to four conclusions. 1) the distribution of keywords follows classic power law; 2) distinct tagging communities are identifiable; 3) the most frequently used tags are situated on a general-specific axis; and 4) nine distinct tagging strategies are observed. These four conclusions are put into perspective collectively in respect of a number of more general and theoretical considerations concerning folksonomies and the classification systems of the future.

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Abstract

This paper proposes a conceptual framework to recast a folksonomy as a Web classification and to use this to explore the ways in which people work with it in assessing, sharing, and navigating Web resources. The author uses information scent and foraging theory as a context to discuss how folksonomy is constructed through interactions among users, a folksonomic system, and a given domain that consists of a group of users who share the same interest or goals. The discussion centers on two dimensions of folksonomies: (1) folksonomy as a Web classification which puts like information together in a Web context; and (2) folksonomy as information scent which helps users to find related resources and users, and obtain desired information. This paper aims to integrate these two dimensions with a conceptual framework that addresses the structure of a folksonomy shaped by users' interactions. A proposed framework consists of three components of users' interactions with a folksonomy: (a) tagging - cognitive categorization of Web accessible resources by an individual user; (b) navigation - exploration and discovery of Web accessible resources in the folksonomic system; and (c) knowledge sharing - representation and communication of knowledge within a domain. This understanding will help us motivate possible future directions of research in folksonomy. This initial framework will frame a number of research questions and help lay the groundwork for future empirical research which focuses on qualitative analysis of a folksonomy and users' tagging behaviors.

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Abstract

Social tagging systems, known as "folksonomies," represent an important part of web resource discovery as they enable free and unrestricted browsing through information space. Folksonomies consisting of subject designators (tags) assigned by users, however, have one important drawback: they do not express semantic relationships, either hierarchical or associative, between tags. As a consequence, the use of tags to browse information resources requires moving from one resource to another, based on coincidence and not on the pre-established meaningful or logical connections that may exist between related resources. We suggest that the semantic structure of the Universal Decimal Classification (UDC) may be used in complementing and supporting tag-based browsing. In this work, two specific questions were investigated: 1) Are terms used as tags in folksonomies included in the UDC?; and, 2) Which facets of UDC match the characteristics of documents or information objects that are tagged in folksonomies? A collection of the most popular tags from Amazon, LibraryThing, Delicious, and 43Things was investigated. The universal nature of UDC was examined through the universality of topics and facets covering diverse human interests which are at the same time interconnected and form a rich and intricate semantic structure. The results suggest that UDC-supported folksonomies could be implemented in resource discovery, in particular in library portals and catalogues.

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Abstract

In recent years, there has been a rapid growth of user-generated data in collaborative tagging (a.k.a. folksonomy-based) systems due to the prevailing of Web 2.0 communities. To effectively assist users to find their desired resources, it is critical to understand user behaviors and preferences. Tag-based profile techniques, which model users and resources by a vector of relevant tags, are widely employed in folksonomy-based systems. This is mainly because that personalized search and recommendations can be facilitated by measuring relevance between user profiles and resource profiles. However, conventional measurements neglect the sentiment aspect of user-generated tags. In fact, tags can be very emotional and subjective, as users usually express their perceptions and feelings about the resources by tags. Therefore, it is necessary to take sentiment relevance into account into measurements. In this paper, we present a novel generic framework SenticRank to incorporate various sentiment information to various sentiment-based information for personalized search by user profiles and resource profiles. In this framework, content-based sentiment ranking and collaborative sentiment ranking methods are proposed to obtain sentiment-based personalized ranking. To the best of our knowledge, this is the first work of integrating sentiment information to address the problem of the personalized tag-based search in collaborative tagging systems. Moreover, we compare the proposed sentiment-based personalized search with baselines in the experiments, the results of which have verified the effectiveness of the proposed framework. In addition, we study the influences by popular sentiment dictionaries, and SenticNet is the most prominent knowledge base to boost the performance of personalized search in folksonomy.

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Date

5. 1.2008 19:22:48

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Date

1. 8.2008 12:39:22

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Abstract

Libraries, private and public, offer valuable resources to library patrons. As of today, the only way to locate information archived exclusively in libraries is through their catalogs. Library patrons, however, often find it difficult to formulate a proper query, which requires using specific keywords assigned to different fields of desired library catalog records, to obtain relevant results. These improperly formulated queries often yield irrelevant results or no results at all. This negative experience in dealing with existing library systems turns library patrons away from directly querying library catalogs; instead, they rely on Web search engines to perform their searches first, and upon obtaining the initial information (e.g., titles, subject headings, or authors) on the desired library materials, they query library catalogs. This searching strategy is an evidence of failure of today's library systems. In solving this problem, we propose an enhanced library system, which allows partial, similarity matching of (a) tags defined by ordinary users at a folksonomy site that describe the content of books and (b) unrestricted keywords specified by an ordinary library patron in a query to search for relevant library catalog records. The proposed library system allows patrons posting a query Q using commonly used words and ranks the retrieved results according to their degrees of resemblance with Q while maintaining the query processing time comparable with that achieved by current library search engines.