cgl's citeulike [19 articles]

Abstract

Social bookmarking services have recently gained popularity among Web users. Whereas numerous studies provide a historical account of tagging systems, the authors use their analysis of a domain-specific social bookmarking service called CiteULike to reflect on two metrics for evaluating tagging behavior: tag growth and tag reuse. They examine the relationship between these two metrics and articulate design implications for enhancing social bookmarking services. The authors briefly reflect on their own work developing a social bookmarking service for CiteSeer. ...

Abstract

Many scientists now manage the bulk of their bibliographic information electronically, thereby organizing their publications and citation material from digital libraries. However, a library has been described as “thought in cold storage,� and unfortunately many digital libraries can be cold, impersonal, isolated, and inaccessible places. In this Review, we discuss the current chilly state of digital libraries for the computational biologist, including PubMed, IEEE Xplore, the ACM digital library, ISI Web of Knowledge, Scopus, Citeseer, arXiv, DBLP, and Google Scholar. We ...

Abstract

BACKGROUND: Academic social tagging systems, such as Connotea and CiteULike, provide researchers with a means to organize personal collections of online references with keywords (tags) and to share these collections with others. One of the side-effects of the operation of these systems is the generation of large, publicly accessible metadata repositories describing the resources in the collections. In light of the well-known expansion of information in the life sciences and the need for metadata to enhance its value, these repositories present ...

Abstract

Recent years have witnessed the emergence of a new class of social networks, which require us to move beyond previously employed representations of complex graph structures. A notable example is that of the folksonomy, an online process where users collaboratively employ tags to resources to impart structure to an otherwise undifferentiated database. In a recent paper, we proposed a mathematical model that represents these structures as tripartite hypergraphs and defined basic topological quantities of interest. In this paper, we extend our ...

Abstract

This paper examines the context of online indexing from the viewpoint of three different groups: users, authors, and intermediaries. User, author and intermediary keywords were collected from journal articles tagged on citeulike and analysed. Descriptive statistics and thesaural term comparison shows that there are important differences in the context of keywords from the three groups. ...

Abstract

Recently, collaborative tagging has become more and more popular in the Web2.0 community, since tags in these Web2.0 systems reflect the specific content features of the resources. This paper presents a recommender for scientific literatures based on semantic concept similarity computed from the collaborative tags. User profiles and item profiles are presented by these semantic concepts, and neighbor users are selected using collaborative filtering. Then, content-based filtering approach is used to generate recommendation list from the papers these neighbor users tagged. ...

Abstract

The high potential of knowledge to create economies of scale attracted the interest towards understanding the dynamics of its diffusion. The new developments in the collaborative and participatory role of web emerges new knowledge structures driving the need towards web based indicators for studying the diffusion of knowledge on web. We present the results of an exploratory case-study investigating the tagging and citing practices for the WWW `06 conference papers. We observed two important patterns: (1) Papers which got heavily tagged ...

Abstract

This paper presents the results of practical studies comparing five well established social classification services for tagging of bookmarks (del.icio.us, BibSonomy bookmarks) and publications (BibSonomy publications, CiteULike, Connotea) in the context of service interoperability and integration. Contrary to most of current research we exclusively focus on the usage of RSS feeds for retrieval of tag-related data. Here we exploit “recent” feeds, as this method of data retrieval corresponds directly to the way users can retrieve data from these services, e.g. for ...

Abstract

A longstanding area of study in indexing is the identification of factors affecting vocabulary usage and consistency. This topic has seen a recent resurgence with a focus on social tagging. Tagging data for scholarly articles made available by the social bookmarking Website CiteULike () were used to test the use of inter-indexer/tagger consistency density values, based on a method developed by the authors by comparing calculations for highly tagged documents representing three subject areas (Science, Social Science, Social Software). The analysis ...

Abstract

Social (or folksonomic) tagging has become a very popular way to describe, categorise, search, discover and navigate content within Web 2.0 websites. Unlike taxonomies, which overimpose a hierarchical categorisation of content, folksonomies empower end users by enabling them to freely create and choose the categories (in this case, tags) that best describe some content. However, as tags are informally defined, continually changing, and ungoverned, social tagging has often been criticised for lowering, rather than increasing, the efficiency of searching, due to ...

Abstract

Collaborative tagging systems pose new challenges to the developers of recommender systems. As observed by recent research, traditional implementations of classic recommender approaches, such as collaborative filtering, are not working well in this new context. To address these challenges, a number of research groups worldwide work on adapting these approaches to the specific nature of collaborative tagging systems. In joining this stream of research, we have developed and compared three variants of user-based collaborative filtering algorithms to provide recommendations of articles ...

Abstract

CiteULike is a collaborative tagging web site which lets users enter academic references into a database and describe these references using tags (categorizations of their own choosing). We looked at the tagging behavior of people who were describing four frequently entered references. We found that while people tend to agree on a few select tags, people also tend to use many variants of these tags. This lack of consensus means that the collaborative aspect of tagging is not as strong as ...

Abstract

We describe the use of the social reference management website CiteULike for recommending scientific articles to users, based on their reference library. We test three different collaborative filtering algorithms, and find that user-based filtering performs best. A temporal analysis of the data indexed by CiteULike shows that it takes about two years for the cold-start problem to disappear and recommendation performance to improve. ...

Abstract

Recent growth of social classification systems due to steadily increasing popularity has established a multitude of heterogeneous isolated, non-integrated, and non-interoperable tag spaces. Contrary to current research predominantly focusing on single folksonomies, we exploit cross-space similarities to improve a variety of tagging use cases beyond the limits of one folksonomy. This paper presents the results of practical studies concerning cross-space analysis of (co-)tag spaces of five well-established social classification services for tagging of bookmarks (del.icio.us, BibSonomy bookmarks), and publications (BibSonomy publications, ...

Abstract

Tags are user-generated labels for entities. Existing research on tag recommendation either focuses on improving its accuracy or on automating the process, while ignoring the efficiency issue. We propose a highly-automated novel framework for real-time tag recommendation. The tagged training documents are treated as triplets of (words, docs, tags), and represented in two bipartite graphs, which are partitioned into clusters by Spectral Recursive Embedding (SRE). Tags in each topical cluster are ranked by our novel ranking algorithm. A two-way Poisson Mixture ...

Abstract

To improve existing social bookmarking systems and to design new ones, researchers and practitioners need to understand how to evaluate tagging behavior. In this paper, we analyze over two years of data from CiteULike, a social bookmarking system for tagging academic papers. We propose six tag metrics-tag growth, tag reuse, tag non-obviousness, tag discrimination, tag frequency, and tag patterns-to understand the characteristics of a social bookmarking system. Using these metrics, we suggest possible design heuristics to implement a social bookmarking system ...

Abstract

Tagging communities are popular instances of a broad class of online communities based on user-generated content. In these communities users introduce and tag content for later use. Although recent studies advocate and attempt to harness social knowledge generated in this context, little research has been done to quantify the current level of user collaboration in these communities. This paper introduces two metrics to quantify the level of collaboration: content reuse and shared interest. Using these two metrics, this paper shows that ...

Abstract

We analyze CiteULike, an online collaborative tagging system where users bookmark and annotate scientific papers. Such a system can be naturally represented as a tri-partite graph whose nodes represent papers, users and tags connected by individual tag assignments. The semantics of tags is studied here, in order to uncover the hidden relationships between tags. We find that the clustering coefficient can be used to analyze the semantical patterns among tags. ...