http://www.bibsonomy.org/burst/tag/vocabularyBibSonomy BuRST Feed for /tag/vocabulary2008-10-16T09:03:33+02:00tagging, communities, vocabulary, evolutionhttp://www.bibsonomy.org/bibtex/2582641c05e7a0b9396945a951822c83f/mschubermschuber2008-09-24T13:53:11+02:00tags reading-group 2006 vocabulary navigation types lab-meeting <span style="color:#555555;">Shilad <a href="http://www.bibsonomy.org/author/Sen">Sen</a> und Shyong K. <a href="http://www.bibsonomy.org/author/Lam">Lam</a> und Al Mamunur <a href="http://www.bibsonomy.org/author/Rashid">Rashid</a> und Dan <a href="http://www.bibsonomy.org/author/Cosley">Cosley</a> und Dan <a href="http://www.bibsonomy.org/author/Frankowski">Frankowski</a> und Jeremy <a href="http://www.bibsonomy.org/author/Osterhouse">Osterhouse</a> und F. <a href="http://www.bibsonomy.org/author/Maxwell Harper">Maxwell Harper</a> und John <a href="http://www.bibsonomy.org/author/Riedl">Riedl</a> </span><em>CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work, </em><em>Seite181--190. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2006</em>)Wed Sep 24 13:53:11 CEST 2008New York, NY, USACSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work181--190tagging, communities, vocabulary, evolution2006tags reading-group 2006 vocabulary navigation types lab-meeting A tagging community’s vocabulary of tags forms the basis for social navigation and shared expression. We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system. We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms’ effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.tagging, communities, vocabulary, evolutionhttp://www.bibsonomy.org/bibtex/2582641c05e7a0b9396945a951822c83f/steff83steff832008-09-16T12:59:44+02:00communities vocabulary tagging master_thesis community folksonomy_background folksonomy folksonomies evolution <span style="color:#555555;">Shilad <a href="http://www.bibsonomy.org/author/Sen">Sen</a> und Shyong K. <a href="http://www.bibsonomy.org/author/Lam">Lam</a> und Al Mamunur <a href="http://www.bibsonomy.org/author/Rashid">Rashid</a> und Dan <a href="http://www.bibsonomy.org/author/Cosley">Cosley</a> und Dan <a href="http://www.bibsonomy.org/author/Frankowski">Frankowski</a> und Jeremy <a href="http://www.bibsonomy.org/author/Osterhouse">Osterhouse</a> und F. <a href="http://www.bibsonomy.org/author/Maxwell Harper">Maxwell Harper</a> und John <a href="http://www.bibsonomy.org/author/Riedl">Riedl</a> </span><em>CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work, </em><em>Seite181--190. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2006</em>)Tue Sep 16 12:59:44 CEST 2008New York, NY, USACSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work181--190tagging, communities, vocabulary, evolution2006communities vocabulary tagging master_thesis community folksonomy_background folksonomy folksonomies evolution A tagging community's vocabulary of tags forms the basis for social navigation and shared expression.We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system.We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms 'effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.Leitlinienwartunghttp://www.bibsonomy.org/bibtex/2918b6d72d74a0008e2ec431c7d820f5f/magermager2008-08-12T10:26:05+02:00Controlled MEDLINE; Databases, Abstracting Vocabulary Review Health Bibliographic/utilization; and Storage Indexing; Information Meta-Analysis; Research/methods; Literature; Trials; Services Humans; Randomized Retrieval/methods; Periodicals; <span style="color:#555555;">P. <a href="http://www.bibsonomy.org/author/Royle">Royle</a> und N. <a href="http://www.bibsonomy.org/author/Waugh">Waugh</a> </span><em>BMC medical research methodology</em><em>Jul 232005. </em><em>LR: 20061115; PUBM: Electronic; DEP: 20050723; JID: 100968545; 2005/02/05 [received]; 2005/07/23 [accepted]; 2005/07/23 [aheadofprint]; epublish . </em>Tue Aug 12 10:26:05 CEST 2008BMC medical research methodologyJul 23LR: 20061115; PUBM: Electronic; DEP: 20050723; JID: 100968545; 2005/02/05 [received]; 2005/07/23 [accepted]; 2005/07/23 [aheadofprint]; epublish23A simplified search strategy for identifying randomised controlled trials for systematic reviews of health care interventions: a comparison with more exhaustive strategies52005Controlled MEDLINE; Databases, Abstracting Vocabulary Review Health Bibliographic/utilization; and Storage Indexing; Information Meta-Analysis; Research/methods; Literature; Trials; Services Humans; Randomized Retrieval/methods; Periodicals; BACKGROUND: It is generally believed that exhaustive searches of bibliographic databases are needed for systematic reviews of health care interventions. The CENTRAL database of controlled trials (RCTs) has been built up by exhaustive searching. The CONSORT statement aims to encourage better reporting, and hence indexing, of RCTs. Our aim was to assess whether developments in the CENTRAL database, and the CONSORT statement, mean that a simplified RCT search strategy for identifying RCTs now suffices for systematic reviews of health care interventions. METHODS: RCTs used in the Cochrane reviews were identified. A brief RCT search strategy (BRSS), consisting of a search of CENTRAL, and then for variants of the word random across all fields (random$.af.) in MEDLINE and EMBASE, was devised and run. Any trials included in the meta-analyses, but missed by the BRSS, were identified. The meta-analyses were then re-run, with and without the missed RCTs, and the differences quantified. The proportion of trials with variants of the word random in the title or abstract was calculated for each year. The number of RCTs retrieved by searching with "random$.af." was compared to the highly sensitive search strategy (HSSS). RESULTS: The BRSS had a sensitivity of 94%. It found all journal RCTs in 47 of the 57 reviews. The missing RCTs made some significant differences to a small proportion of the total outcomes in only five reviews, but no important differences in conclusions resulted. In the post-CONSORT years, 1997-2003, the percentage of RCTs with random in the title or abstract was 85%, a mean increase of 17% compared to the seven years pre-CONSORT (95% CI, 8.3% to 25.9%). The search using random$.af. reduced the MEDLINE retrieval by 84%, compared to the HSSS, thereby reducing the workload of checking retrievals. CONCLUSION: A brief RCT search strategy is now sufficient to locate RCTs for systematic reviews in most cases. Exhaustive searching is no longer cost-effective, because in effect it has already been done for CENTRAL.http://www.bibsonomy.org/bibtex/2cc39f6a45134020d97fe0fdce7793691/vittorio.loretovittorio.loreto2008-06-19T13:58:51+02:00information vocabulary heaps 1978 retrieval growth <span style="color:#555555;">H. S. <a href="http://www.bibsonomy.org/author/Heaps">Heaps</a> </span><em>Academic Press, Inc., </em><em>Orlando, FL, USA, </em>(<em>1978</em>)Thu Jun 19 13:58:51 CEST 2008Orlando, FL, USAInformation Retrieval: Computational and Theoretical Aspects1978information vocabulary heaps 1978 retrieval growth http://www.bibsonomy.org/bibtex/2e157ee6010babd7cfd826aee0e25914d/brightbytebrightbyte2008-05-22T23:40:58+02:00knowledge vocabulary information-retrieval ontology SKOS <span style="color:#555555;">Alistair <a href="http://www.bibsonomy.org/author/Miles">Miles</a> </span>(<em>2006</em>)Thu May 22 23:40:58 CEST 2008A Theory of Retrieval Using Structured Vocabularies2006knowledge vocabulary information-retrieval ontology SKOS A primary motivation for the development of the Semantic Web has been the need for effective information retrieval systems which may be realised through vocabulary control and the use of structured metadata. The technological framework of the Web (URI, HTTP, XML) and of the Semantic Web (RDF, OWL, SPARQL) provides a platform upon which distributed data and metadata applications may be constructed, but does not in itself provide any direct support for information retrieval applications per se. Widely applicable Semantic Web languages that extend this basic layer and provide generic support for retrieval applications, in addition to good practice guidelines and design patterns for developing such applications, are required. The ultimate purpose of this report is to develop a formal theory of retrieval using controlled vocabularies that have a simple and intuitive structure, to provide the necessary theoretical foundations for the development of Semantic Web languages and design patterns for distributed retrieval applications. The main body of this report is devoted to the articulation of such a theory. The theory is expressed formally through the use of mathematical notation, with the intention that this level of formality will provide the bridge between informal requirements specifications and the implementation of effective retrieval applications in computer systems. Specifically, a theory is developed to describe the ways in which a structured vocabulary may be used to construct an index over a collection of objects and then used to express queries which may be evaluated against an index to obtain a set of results. This theory is extended to consider ways in which both the precision and recall of retrieval strategies may be improved, through the use of expansion and ranking techniques and through “coordination”. The problem of translating between controlled vocabularies is also considered. The theory attempts to formalise, unify and extend the traditional wisdom of the library sciences regarding the use of thesauri, classification schemes, subject heading systems, taxonomies and other types of structured vocabulary, so that proven techniques and methodologies may be transferred to a Semantic Web context. The recently chartered W3C Semantic Web Deployment Working Group has been charged with the development of the Simple Knowledge Organisation System (SKOS) to W3C Recommendation status. SKOS is a Semantic Web language specifically intended to support information retrieval applications using controlled vocabularies that have a relatively simple structure. A formal requirements specification is the first planned deliverable in the standardisation of SKOS. An immediate goal of this report is to provide a level of abstraction that can be used to perform a comparative analysis of use cases involving information retrieval systems that operate with structured vocabularies, so that the requirements of these systems with respect to Semantic Web languages such as SKOS may be clearly determined. Also, this report suggests ways in which the theory may be mapped to concrete language constructs and representation patterns in Semantic Web languages. In so doing it is hoped that the development of SKOS and similar languages may be grounded with sufficient rigour to ensure their wide applicability and consistent use.Vocabulary growth in collaborative tagging systemshttp://www.bibsonomy.org/bibtex/2fb163dd424fa1eb40640340f27ee0ea4/dbenzdbenz2008-04-14T09:35:08+02:00vocabulary folksonomy toread analysis <span style="color:#555555;">Ciro <a href="http://www.bibsonomy.org/author/Cattuto">Cattuto</a> und Andrea <a href="http://www.bibsonomy.org/author/Baldassarri">Baldassarri</a> und Vito D. P. <a href="http://www.bibsonomy.org/author/Servedio">Servedio</a> und Vittorio <a href="http://www.bibsonomy.org/author/Loreto">Loreto</a> </span>(<em>2007</em>)Mon Apr 14 09:35:08 CEST 2008Vocabulary growth in collaborative tagging systems2007vocabulary folksonomy toread analysis We analyze a large-scale snapshot of del.icio.us and investigate how the number of different tags in the system grows as a function of a suitably defined notion of time. We study the temporal evolution of the global vocabulary size, i.e. the number of distinct tags in the entire system, as well as the evolution of local vocabularies, that is the growth of the number of distinct tags used in the context of a given resource or user. In both cases, we find power-law behaviors with exponents smaller than one. Surprisingly, the observed growth behaviors are remarkably regular throughout the entire history of the system and across very different resources being bookmarked. Similar sub-linear laws of growth have been observed in written text, and this qualitative universality calls for an explanation and points in the direction of non-trivial cognitive processes in the complex interaction patterns characterizing collaborative tagging.tagging, communities, vocabulary, evolutionhttp://www.bibsonomy.org/bibtex/2582641c05e7a0b9396945a951822c83f/stummestumme2008-03-10T20:03:40+01:00communities vocabulary tagging community folksonomy folksonomies evolution <span style="color:#555555;">Shilad <a href="http://www.bibsonomy.org/author/Sen">Sen</a> und Shyong K. <a href="http://www.bibsonomy.org/author/Lam">Lam</a> und Al Mamunur <a href="http://www.bibsonomy.org/author/Rashid">Rashid</a> und Dan <a href="http://www.bibsonomy.org/author/Cosley">Cosley</a> und Dan <a href="http://www.bibsonomy.org/author/Frankowski">Frankowski</a> und Jeremy <a href="http://www.bibsonomy.org/author/Osterhouse">Osterhouse</a> und F. <a href="http://www.bibsonomy.org/author/Maxwell Harper">Maxwell Harper</a> und John <a href="http://www.bibsonomy.org/author/Riedl">Riedl</a> </span><em>CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work, </em><em>Seite181--190. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2006</em>)Mon Mar 10 20:03:40 CET 2008New York, NY, USACSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work181--190tagging, communities, vocabulary, evolution2006communities vocabulary tagging community folksonomy folksonomies evolution A tagging community's vocabulary of tags forms the basis for social navigation and shared expression.We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system.We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms 'effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.tagging, communities, vocabulary, evolutionhttp://www.bibsonomy.org/bibtex/2582641c05e7a0b9396945a951822c83f/hothohotho2008-01-25T19:57:49+01:00vocabulary tagging tag summerschool analysis kdubiq evolution <span style="color:#555555;">Shilad <a href="http://www.bibsonomy.org/author/Sen">Sen</a> und Shyong K. <a href="http://www.bibsonomy.org/author/Lam">Lam</a> und Al Mamunur <a href="http://www.bibsonomy.org/author/Rashid">Rashid</a> und Dan <a href="http://www.bibsonomy.org/author/Cosley">Cosley</a> und Dan <a href="http://www.bibsonomy.org/author/Frankowski">Frankowski</a> und Jeremy <a href="http://www.bibsonomy.org/author/Osterhouse">Osterhouse</a> und F. <a href="http://www.bibsonomy.org/author/Maxwell Harper">Maxwell Harper</a> und John <a href="http://www.bibsonomy.org/author/Riedl">Riedl</a> </span><em>CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work, </em><em>Seite181--190. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2006</em>)Fri Jan 25 19:57:49 CET 2008New York, NY, USACSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work181--190tagging, communities, vocabulary, evolution2006vocabulary tagging tag summerschool analysis kdubiq evolution A tagging community's vocabulary of tags forms the basis for social navigation and shared expression.We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system.We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms 'effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.http://www.bibsonomy.org/bibtex/2eaef17fef76ad3152f0300a5e9d5ddae/hothohotho2007-12-20T08:50:04+01:00vocabulary controlled folksonomy toread ontology <span style="color:#555555;">Alireza <a href="http://www.bibsonomy.org/author/Noruzi">Noruzi</a> </span><em>Webology</em>(<em>2007</em>)Thu Dec 20 08:50:04 CET 2007Webology2{Folksonomies: Why do we need controlled vocabulary?}42007vocabulary controlled folksonomy toread ontology http://www.bibsonomy.org/bibtex/27afc928bc2568eb4a701598f4a9e8c3d/perceptronperceptron2007-12-16T20:00:22+01:00Frontal Non-U.S. Vocabulary Gyrus Male; Adult; Gov't, Humans; Emission-Computed; Phonetics; Brain; Cortex; Research Cerebellum; Support, Motor Non-P.H.S.; Tomography, Reading; Gov't; Cinguli; U.S. P.H.S.; Lobe; Female; <span style="color:#555555;">J. A. <a href="http://www.bibsonomy.org/author/Fiez">Fiez</a> und D. A. <a href="http://www.bibsonomy.org/author/Balota">Balota</a> und M. E. <a href="http://www.bibsonomy.org/author/Raichle">Raichle</a> und S. E. <a href="http://www.bibsonomy.org/author/Petersen">Petersen</a> </span><em>Neuron</em>(<em>1999</em>)Sun Dec 16 20:00:22 CET 2007Neuron205--218Effects of lexicality, frequency, and spelling-to-sound consistency on the functional anatomy of reading.241999Frontal Non-U.S. Vocabulary Gyrus Male; Adult; Gov't, Humans; Emission-Computed; Phonetics; Brain; Cortex; Research Cerebellum; Support, Motor Non-P.H.S.; Tomography, Reading; Gov't; Cinguli; U.S. P.H.S.; Lobe; Female; Functional neuroimaging was used to investigate three factors that affect reading performance: first, whether a stimulus is a word or pronounceable non-word (lexicality), second, how often a word is encountered (frequency), and third, whether the pronunciation has a predictable spelling-to-sound correspondence (consistency). Comparisons between word naming (reading) and visual fixation scans revealed stimulus-related activation differences in seven regions. A left frontal region showed effects of consistency and lexicality, indicating a role in orthographic to phonological transformation. Motor cortex showed an effect of consistency bilaterally, suggesting that motoric processes beyond high-level representations of word phonology influence reading performance. Implications for the integration of these results into theoretical models of word reading are discussed.http://www.bibsonomy.org/bibtex/287701d38906e3b36cb5cd45a0884f6ee/krasskrass2007-12-05T11:37:36+01:00thesaurus definition vocabulary taxonomy <span style="color:#555555;">Woody <a href="http://www.bibsonomy.org/author/Pidcock">Pidcock</a> </span><em>January2003. </em>Wed Dec 05 11:37:36 CET 2007JanuaryWhat are the differences between a vocabulary, a taxonomy, a thesaurus, an ontology, and a meta-model?2003thesaurus definition vocabulary taxonomy This excellent overview was contributed by Woody Pidcock of the Boeing company. Many organizations and companies are struggling with these terms and the ideas behind them; this set of definitions will help to clarify.Vocabulary growth in collaborative tagging systemshttp://www.bibsonomy.org/bibtex/24d6bfbd16ba976f4a4aae985c2a92449/hothohotho2007-12-04T10:29:43+01:00systems collaborative vocabulary tagging web 2.0 <span style="color:#555555;">Ciro <a href="http://www.bibsonomy.org/author/Cattuto">Cattuto</a> und Andrea <a href="http://www.bibsonomy.org/author/Baldassarri">Baldassarri</a> und Vito D. P. <a href="http://www.bibsonomy.org/author/Servedio">Servedio</a> und Vittorio <a href="http://www.bibsonomy.org/author/Loreto">Loreto</a> </span>(<em>2007</em>)Tue Dec 04 10:29:43 CET 2007Vocabulary growth in collaborative tagging systems2007systems collaborative vocabulary tagging web 2.0 http://www.bibsonomy.org/bibtex/2ebe2a6c94b0d0d0a5dd4a59dc98e0f4f/iswc2007iswc20072007-11-07T19:17:05+01:00iswc workshop_esoe system 2007 pattern collaborative vocabulary indexing free-for-all <span style="color:#555555;">Wolfgang <a href="http://www.bibsonomy.org/author/Maass">Maass</a> und Tobias <a href="http://www.bibsonomy.org/author/Kowatsch">Kowatsch</a> und Timo <a href="http://www.bibsonomy.org/author/Münster">M&#252;nster</a> </span><em>Proceedings of the International Workshop on Emergent Semantics and Ontology Evolution (ESOE2007) at ISWC/ASWC2007, Busan, South Korea, </em><em>November2007. </em>Wed Nov 07 19:17:05 CET 2007Proceedings of the International Workshop on Emergent Semantics and Ontology Evolution (ESOE2007) at ISWC/ASWC2007, Busan, South Koreahttp://data.semanticweb.org/workshop/esoe/2007/proceedingsNovemberVocabulary Patterns in Free-for-all Collaborative Indexing Systems2007iswc workshop_esoe system 2007 pattern collaborative vocabulary indexing free-for-all In collaborative indexing systems users generate a big amount of metadata by labelling web-based content. These labels are known as tags and form a shared vocabulary. In order to understand the characteristics of that vocabulary, we study structural patterns of these tags by implying the theory of self-organizing systems. Therefore, we utilize the graph theoretic notion to model the network of tags and their valued connections, which represent frequency rates of co-occurring tags. Empirical data is provided by the free-for-all collaborative indexing systems Delicious, Connotea and CiteULike. First, we measure the frequency distribution of co-occurring tags. Secondly, we correlate these tags towards their rank over time. Results indicate a strong relationship among a few tags as well as a notable persistence of these tags over time. Therefore, we make the educated guess that the observed collaborative indexing systems are self-organizing systems towards a shared vocabulary building. Implications on the results are the presence of semantic domains based on high frequency rates of co-occurring tags, which reflect topics of interest among the user community. When observing those semantic domains over time, that information can be used to provide a historical or trend-setting development of the community's interests, thus enhancing collaborative indexing systems in general as well as providing a new tool to develop community-based products and services at the same time.tagging, communities, vocabulary, evolutionhttp://www.bibsonomy.org/bibtex/2582641c05e7a0b9396945a951822c83f/bsmythbsmyth2007-11-05T17:28:31+01:00communities vocabulary tagging reidl evolution <span style="color:#555555;">Shilad <a href="http://www.bibsonomy.org/author/Sen">Sen</a> und Shyong K. <a href="http://www.bibsonomy.org/author/Lam">Lam</a> und Al Mamunur <a href="http://www.bibsonomy.org/author/Rashid">Rashid</a> und Dan <a href="http://www.bibsonomy.org/author/Cosley">Cosley</a> und Dan <a href="http://www.bibsonomy.org/author/Frankowski">Frankowski</a> und Jeremy <a href="http://www.bibsonomy.org/author/Osterhouse">Osterhouse</a> und F. <a href="http://www.bibsonomy.org/author/Maxwell Harper">Maxwell Harper</a> und John <a href="http://www.bibsonomy.org/author/Riedl">Riedl</a> </span><em>CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work, </em><em>Seite181--190. </em><em>New York, NY, USA, </em><em>ACM Press, </em>(<em>2006</em>)Mon Nov 05 17:28:31 CET 2007New York, NY, USACSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work181--190tagging, communities, vocabulary, evolution2006communities vocabulary tagging reidl evolution A tagging community's vocabulary of tags forms the basis for social navigation and shared expression.We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system.We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms 'effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.tagging, communities, vocabulary, evolutionhttp://www.bibsonomy.org/bibtex/2582641c05e7a0b9396945a951822c83f/wnpxrzwnpxrz2007-08-11T10:49:57+02:00vocabulary tagging community imported evolution <span style="color:#555555;">Shilad <a href="http://www.bibsonomy.org/author/Sen">Sen</a> und Shyong K. <a href="http://www.bibsonomy.org/author/Lam">Lam</a> und Al Mamunur <a href="http://www.bibsonomy.org/author/Rashid">Rashid</a> und Dan <a href="http://www.bibsonomy.org/author/Cosley">Cosley</a> und Dan <a href="http://www.bibsonomy.org/author/Frankowski">Frankowski</a> und Jeremy <a href="http://www.bibsonomy.org/author/Osterhouse">Osterhouse</a> und F. <a href="http://www.bibsonomy.org/author/Maxwell Harper">Maxwell Harper</a> und John <a href="http://www.bibsonomy.org/author/Riedl">Riedl</a> </span><em>CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work, </em><em>Seite181--190. </em><em>New York, NY, USA, </em><em>ACM Press, </em>(<em>2006</em>)Sat Aug 11 10:49:57 CEST 2007New York, NY, USACSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work181--190tagging, communities, vocabulary, evolution2006vocabulary tagging community imported evolution A tagging community's vocabulary of tags forms the basis for social navigation and shared expression.We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system.We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms 'effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.http://www.bibsonomy.org/bibtex/23e91851301a3c6a419c2cb415ac717c7/statphys23statphys232007-06-20T10:16:09+02:00networks vocabulary topic-11 scale-free statphys23 language evolution <span style="color:#555555;">A. <a href="http://www.bibsonomy.org/author/Kalampokis">Kalampokis</a> und K. <a href="http://www.bibsonomy.org/author/Kosmidis">Kosmidis</a> und P. <a href="http://www.bibsonomy.org/author/Argyrakis">Argyrakis</a> </span><em>Abstract Book of the XXIII IUPAP International Conference on Statistical Physics, </em><em>Genova, Italy, </em><em>9-13 July2007. </em>Wed Jun 20 10:16:09 CEST 2007Genova, ItalyAbstract Book of the XXIII IUPAP International Conference on Statistical Physics9-13 JulyVocabulary and its evolution on Complex Networks2007networks vocabulary topic-11 scale-free statphys23 language evolution We examine the evolution of the vocabulary of a group of individuals (linguistic agents) on a scale-free network, using Monte Carlo simulations and assumptions from evolutionary game theory. It is known that when the agents are arranged in a two dimensional lattice structure and interact by diffusion and encounter, then their final vocabulary size is the maximum possible. Knowing all available words is essential in order to increase the probability to ``survive'' by effective reproduction. On scale-free networks we find a different result. It is not necessary to learn the entire vocabulary available. Survival chances are increased by using the vocabulary of the ``hubs'' (nodes with high degree). The existence of the ``hubs'' in a scale-free network is the source of an additional important fitness generating mechanism.dblphttp://www.bibsonomy.org/bibtex/2fcd0ebc5ca594176e12fe1a3a3873ca3/kzhoukzhou2007-06-11T14:26:19+02:00vocabulary image Scalable <span style="color:#555555;">David <a href="http://www.bibsonomy.org/author/Nistér">Nist&#233;r</a> und Henrik <a href="http://www.bibsonomy.org/author/Stewénius">Stew&#233;nius</a> </span><em>CVPR (2), </em><em>Seite2161-2168. </em><em>IEEE Computer Society, </em>(<em>2006</em>)Mon Jun 11 14:26:19 CEST 2007CVPR (2)conf/cvpr/20062161-2168Scalable Recognition with a Vocabulary Tree.2006vocabulary image Scalable Vocabulary growth in collaborative tagging systemshttp://www.bibsonomy.org/bibtex/24d6bfbd16ba976f4a4aae985c2a92449/andreabandreab2007-05-22T20:21:53+02:002007 vocabulary tagging myown imported growth <span style="color:#555555;">Ciro <a href="http://www.bibsonomy.org/author/Cattuto">Cattuto</a> und Andrea <a href="http://www.bibsonomy.org/author/Baldassarri">Baldassarri</a> und Vito D. P. <a href="http://www.bibsonomy.org/author/Servedio">Servedio</a> und Vittorio <a href="http://www.bibsonomy.org/author/Loreto">Loreto</a> </span>(<em>2007</em>)Tue May 22 20:21:53 CEST 2007Vocabulary growth in collaborative tagging systems20072007 vocabulary tagging myown imported growth dblphttp://www.bibsonomy.org/bibtex/258d1b4a39ff5d68375c1371ef4d09f62/andreabandreab2007-05-10T17:38:17+02:00zipf d4.1 vocabulary word frequency dictionary tagora simon montemurro distribution growth <span style="color:#555555;">Dami&#225;n H. <a href="http://www.bibsonomy.org/author/Zanette">Zanette</a> und Marcelo A. <a href="http://www.bibsonomy.org/author/Montemurro">Montemurro</a> </span><em>Journal of Quantitative Linguistics</em><em>12(1):29-40</em>(<em>2005</em>)Thu May 10 17:38:17 CEST 2007Journal of Quantitative Linguistics129-40Dynamics of Text Generation with Realistic Zipf's Distribution.122005zipf d4.1 vocabulary word frequency dictionary tagora simon montemurro distribution growth tagging, communities, vocabulary, evolutionhttp://www.bibsonomy.org/bibtex/2582641c05e7a0b9396945a951822c83f/jboy701jboy7012007-04-30T23:53:43+02:00collaborative-tagging vocabulary tagging experiment community evolution <span style="color:#555555;">Shilad <a href="http://www.bibsonomy.org/author/Sen">Sen</a> und Shyong K. <a href="http://www.bibsonomy.org/author/Lam">Lam</a> und Al Mamunur <a href="http://www.bibsonomy.org/author/Rashid">Rashid</a> und Dan <a href="http://www.bibsonomy.org/author/Cosley">Cosley</a> und Dan <a href="http://www.bibsonomy.org/author/Frankowski">Frankowski</a> und Jeremy <a href="http://www.bibsonomy.org/author/Osterhouse">Osterhouse</a> und F. <a href="http://www.bibsonomy.org/author/Maxwell Harper">Maxwell Harper</a> und John <a href="http://www.bibsonomy.org/author/Riedl">Riedl</a> </span><em>CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work, </em><em>Seite181--190. </em><em>New York, NY, USA, </em><em>ACM Press, </em>(<em>2006</em>)Mon Apr 30 23:53:43 CEST 2007New York, NY, USACSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work181--190tagging, communities, vocabulary, evolution2006collaborative-tagging vocabulary tagging experiment community evolution