Bridging ontologies and folksonomies to leverage knowledge sharing on the social Web: A brief survey
---
paper_title: Using Ontologies to Strengthen Folksonomies and Enrich Information Retrieval in Weblogs

paper_content:

While free-tagging classification is widely used in social software implementations and especially in weblogs, it raises various issues regarding information retrieval. In this paper, we describe an approach that mixes folksonomies and semantic web technologies in order to solve some of these problems, and to enrich information retrieval capabilities among blog posts. We first introduce the corporate context of the study and the issues we have faced that motivated our approach. Then, we argue how the use of domain ontologies combined with the SIOC vocabulary on the top of an existing folksonomy and weblogging platform offers a way to get rid of free-tagging classification flaws, and enhances information retrieval by suggesting related blog posts. Aside of the theoretical background, this paper also focuses on implementation. We present experimental results of this approach through the example of add-ons to a corporate blogging platform and the associated semantic web search engine, that extensively uses RDF and other semantic web technologies to find appropriate information and suggest related posts.
---
paper_title: The complex dynamics of collaborative tagging

paper_content:

The debate within the Web community over the optimal means by which to organize information often pits formalized classifications against distributed collaborative tagging systems. A number of questions remain unanswered, however, regarding the nature of collaborative tagging systems including whether coherent categorization schemes can emerge from unsupervised tagging by users. This paper uses data from the social bookmarking site delicio. us to examine the dynamics of collaborative tagging systems. In particular, we examine whether the distribution of the frequency of use of tags for "popular" sites with a long history (many tags and many users) can be described by a power law distribution, often characteristic of what are considered complex systems. We produce a generative model of collaborative tagging in order to understand the basic dynamics behind tagging, including how a power law distribution of tags could arise. We empirically examine the tagging history of sites in order to determine how this distribution arises over time and to determine the patterns prior to a stable distribution. Lastly, by focusing on the high-frequency tags of a site where the distribution of tags is a stabilized power law, we show how tag co-occurrence networks for a sample domain of tags can be used to analyze the meaning of particular tags given their relationship to other tags.
---
paper_title: Ontologies are us: a unified model of social networks and semantics

paper_content:

In our work we extend the traditional bipartite model of ontologies with the social dimension, leading to a tripartite model of actors, concepts and instances. We demonstrate the application of this representation by showing how community-based semantics emerges from this model through a process of graph transformation. We illustrate ontology emergence by two case studies, an analysis of a large scale folksonomy system and a novel method for the extraction of community-based ontologies from Web pages.
---
paper_title: GroupMe! - Where Semantic Web meets Web 2.0

paper_content:

Grouping is an attractive interaction metaphor for users to create reference collections of Web resources they are interested in. Each grouping activity has a certain semantics: things which were previously unrelated are now connected with others via the group. We present the GroupMe! application which allows users to group and arrange multimedia Web resources they are interested in. GroupMe! has an easy-touse interface for gathering and grouping of resources, and allows users to tag everything they like. The semantics of any user interaction is captured, transformed and stored as adequate RDF descriptions. As an example application of this automatically derived RDF content, we show the enhancement of search for tagged Web resources, which evaluates the grouping information to deduce additional contextual information about the resources. GroupMe! is available via http://www.groupme.org.
---
paper_title: Bridging the Gap Between Folksonomies and the Semantic Web: An Experience Report

paper_content:

While folksonomies allow tagging of similar resources with a variety of tags, their content retrieval mechanisms are severely hampered by being agnostic to the relations that exist between these tags. To overcome this limitation, several methods have been proposed to find groups of implicitly inter-related tags. We believe that content retrieval can be further improved by making the relations between tags explicit. In this paper we propose the semantic enrichment of folksonomy tags with explicit relations by harvesting the Semantic Web, i.e., dynamically selecting and combining relevant bits of knowledge from online ontologies. Our experimental results show that, while semantic enrichment needs to be aware of the particular characteristics of folksonomies and the Semantic Web, it is beneficial for both.
---
paper_title: Integrating Folksonomies with the Semantic Web

paper_content:

While tags in collaborative tagging systems serve primarily an indexing purpose, facilitating search and navigation of resources, the use of the same tags by more than one individual can yield a collective classification schema. We present an approach for making explicit the semantics behind the tag space in social tagging systems, so that this collaborative organization can emerge in the form of groups of concepts and partial ontologies. This is achieved by using a combination of shallow pre-processing strategies and statistical techniques together with knowledge provided by ontologies available on the semantic web. Preliminary results on the del.icio.us and Flickr tag sets show that the approach is very promising: it generates clusters with highly related tags corresponding to concepts in ontologies and meaningful relationships among subsets of these tags can be identified.
---
paper_title: Using the Semantic Web as Background Knowledge for Ontology Mapping

paper_content:

While current approaches to ontology mapping produce good results by mainly relying on label and structure based similarity measures, there are several cases in which they fail to discover important mappings. In this paper we describe a novel approach to ontology mapping, which is able to avoid this limitation by using background knowledge. Existing approaches relying on background knowledge typically have one or both of two key limitations: 1) they rely on a manually selected reference ontology; 2) they suffer from the noise introduced by the use of semi-structured sources, such as text corpora. Our technique circumvents these limitations by exploiting the increasing amount of semantic resources available online. As a result, there is no need either for a manually selected reference ontology (the relevant ontologies are dynamically selected from an online ontology repository), or for transforming background knowledge in an ontological form. The promising results from experiments on two real life thesauri indicate both that our approach has a high precision and also that it can find mappings, which are typically missed by existing approaches.
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paper_title: Discovering Shared Conceptualizations in Folksonomies

paper_content:

Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.
---
paper_title: Ontology of Folksonomy: A Mash-Up of Apples and Oranges

paper_content:

Ontologies are enabling technology for the Semantic Web. They are a means for people to state what they mean by the terms used in data that they might generate, share, or consume. Folksonomies are an emergent phenomenon of the social Web. They arise from data about how people associate terms with content that they generate, share, or consume. Recently the two ideas have been put into opposition, as if they were right and left poles of a political spectrum. This is a false dichotomy; they are more like apples and oranges. In fact, as the Semantic Web matures and the social Web grows, there is increasing value in applying Semantic Web technologies to the data of the social Web. This article is an attempt to clarify the distinct roles for ontologies and folksonomies, and preview some new work that applies the two ideas togetherâ€”an ontology of folk-sonomy.
---
paper_title: Using Ontologies to Strengthen Folksonomies and Enrich Information Retrieval in Weblogs

paper_content:

While free-tagging classification is widely used in social software implementations and especially in weblogs, it raises various issues regarding information retrieval. In this paper, we describe an approach that mixes folksonomies and semantic web technologies in order to solve some of these problems, and to enrich information retrieval capabilities among blog posts. We first introduce the corporate context of the study and the issues we have faced that motivated our approach. Then, we argue how the use of domain ontologies combined with the SIOC vocabulary on the top of an existing folksonomy and weblogging platform offers a way to get rid of free-tagging classification flaws, and enhances information retrieval by suggesting related blog posts. Aside of the theoretical background, this paper also focuses on implementation. We present experimental results of this approach through the example of add-ons to a corporate blogging platform and the associated semantic web search engine, that extensively uses RDF and other semantic web technologies to find appropriate information and suggest related posts.
---
paper_title: Extreme Tagging: Emergent Semantics through the Tagging of Tags

paper_content:

While the Semantic Web requires a large amount of structured knowledge (triples) to allow machine reasoning, the acquisition of this knowledge still represents an open issue. Indeed, expressing expert knowledge in a given formalism is a tedious process. Less structured annotations such as tagging have, however, proved immensely popular, whilst existing unstructured or semi-structured collaborative knowledge bases such as Wikipedia have proven to be useful and scalable. Both processes are often regulated through social mechanisms such as wiki-like operations, recommendations, ratings, and collaborative games. To promote collaborative tagging as a means to acquire unstructured as well as structured knowledge we introduce the notion of Extreme Tagging, which describes systems which allow the tagging of resources, as well as of tags themselves and their relations. We provide a formal description of extreme tagging followed by examples and highlight the necessity of regulatory processes which can be applied to it. We also present a prototype implementation.
---
paper_title: Using Ontologies to Strengthen Folksonomies and Enrich Information Retrieval in Weblogs

paper_content:

While free-tagging classification is widely used in social software implementations and especially in weblogs, it raises various issues regarding information retrieval. In this paper, we describe an approach that mixes folksonomies and semantic web technologies in order to solve some of these problems, and to enrich information retrieval capabilities among blog posts. We first introduce the corporate context of the study and the issues we have faced that motivated our approach. Then, we argue how the use of domain ontologies combined with the SIOC vocabulary on the top of an existing folksonomy and weblogging platform offers a way to get rid of free-tagging classification flaws, and enhances information retrieval by suggesting related blog posts. Aside of the theoretical background, this paper also focuses on implementation. We present experimental results of this approach through the example of add-ons to a corporate blogging platform and the associated semantic web search engine, that extensively uses RDF and other semantic web technologies to find appropriate information and suggest related posts.
---
paper_title: Ontology of Folksonomy: A Mash-Up of Apples and Oranges

paper_content:

Ontologies are enabling technology for the Semantic Web. They are a means for people to state what they mean by the terms used in data that they might generate, share, or consume. Folksonomies are an emergent phenomenon of the social Web. They arise from data about how people associate terms with content that they generate, share, or consume. Recently the two ideas have been put into opposition, as if they were right and left poles of a political spectrum. This is a false dichotomy; they are more like apples and oranges. In fact, as the Semantic Web matures and the social Web grows, there is increasing value in applying Semantic Web technologies to the data of the social Web. This article is an attempt to clarify the distinct roles for ontologies and folksonomies, and preview some new work that applies the two ideas togetherâ€”an ontology of folk-sonomy.
---
paper_title: Meaning Of A Tag: A collaborative approach to bridge the gap between tagging and Linked Data

paper_content:

This paper introduces MOAT, a lightweight Semantic Web framework that provides a collaborative way to let Web 2.0 content producers give meanings to their tags in a machine- readable way. To achieve this goal, this approach relies on Linked Data principles, using URIs from existing resources to define these meanings. That way, users can create inter- linked RDF data and let their content enter the Semantic Web, while solving some limits of free-tagging at the same time.
---
paper_title: Ontogame: Weaving the semantic web by online gaming

paper_content:

Most of the challenges faced when building the Semantic Web require a substantial amount of human labor and intelligence. Despite significant advancement in ontology learning and human language technology, the tasks of ontology construction, semantic annotation, and establishing alignments between multiple ontologies remain highly dependent on human intelligence. This means that individuals need to contribute time and sometimes other resources. Unfortunately, we observe a serious lack of user involvement in the aforementioned tasks, which may be due to the absence of motivations for people who contribute. As a novel solution, we (1) propose to masquerade the core tasks of weaving the Semantic Web behind online, multi-player game scenarios, in order to create proper incentives for human users to get involved. Doing so, we adopt the findings from the already famous "games with a purpose" by von Ahn, who has shown that presenting a useful task, which requires human intelligence, in the form of an online game can motivate a large amount of people to work heavily on this task, and this for free. Then, we (2) describe our generic OntoGame platform, and (3) several gaming scenarios for various tasks plus our respective prototypes. Based on the analysis of user data and interviews with players, we provide preliminary evidence that users (4) enjoy the games and are willing to dedicate their time to those games, (5) are able to produce high-quality conceptual choices. Eventually we show how users entertaining themselves by online games can unknowingly help weave and maintain the Semantic Web.
---
paper_title: Extreme Tagging: Emergent Semantics through the Tagging of Tags

paper_content:

While the Semantic Web requires a large amount of structured knowledge (triples) to allow machine reasoning, the acquisition of this knowledge still represents an open issue. Indeed, expressing expert knowledge in a given formalism is a tedious process. Less structured annotations such as tagging have, however, proved immensely popular, whilst existing unstructured or semi-structured collaborative knowledge bases such as Wikipedia have proven to be useful and scalable. Both processes are often regulated through social mechanisms such as wiki-like operations, recommendations, ratings, and collaborative games. To promote collaborative tagging as a means to acquire unstructured as well as structured knowledge we introduce the notion of Extreme Tagging, which describes systems which allow the tagging of resources, as well as of tags themselves and their relations. We provide a formal description of extreme tagging followed by examples and highlight the necessity of regulatory processes which can be applied to it. We also present a prototype implementation.
---
paper_title: Towards Semantically-Interlinked Online Communities

paper_content:

Online community sites have replaced the traditional means of keeping a community informed via libraries and publishing. At present, online communities are islands that are not interlinked. We describe different types of online communities and tools that are currently used to build and support such communities. Ontologies and Semantic Web technologies offer an upgrade path to providing more complex services. Fusing information and inferring links between the various applications and types of information provides relevant insights that make the available information on the Internet more valuable. We present the SIOC ontology which combines terms from vocabularies that already exist with new terms needed to describe the relationships between concepts in the realm of online community sites.
---
paper_title: GroupMe! - Where Semantic Web meets Web 2.0

paper_content:

Grouping is an attractive interaction metaphor for users to create reference collections of Web resources they are interested in. Each grouping activity has a certain semantics: things which were previously unrelated are now connected with others via the group. We present the GroupMe! application which allows users to group and arrange multimedia Web resources they are interested in. GroupMe! has an easy-touse interface for gathering and grouping of resources, and allows users to tag everything they like. The semantics of any user interaction is captured, transformed and stored as adequate RDF descriptions. As an example application of this automatically derived RDF content, we show the enhancement of search for tagged Web resources, which evaluates the grouping information to deduce additional contextual information about the resources. GroupMe! is available via http://www.groupme.org.
---
paper_title: Tag Mediated Society with SCOT Ontology

paper_content:

In this paper we give an overview of the int.ere.st for a social tagging, bookmarking, and sharing service. It is based on the SCOT ontology. The SCOT ontology can represent the structure and semantics for social tagging data and provide methods for sharing and reusing them. We describe how it enables users to participate in a semantic social tagging from functional point of view and show how int.ere.st allows users to save, tag, and search SCOT ontologies. All kinds of user contributions in the system will be exposed as RDF vocabularies that connect them. We believe it is a good starting point to build Semantic Web based society using tagging data.
---
paper_title: mle: Enhancing the Exploration of Mailing List Archives Through Making Semantics Explicit

paper_content:

Following and understanding discussions on mailing lists is a prevalent task for executives and policy makers in order to get an impression of one's company image. However, existing solutions providing a Web-based archive require substantial manual effort to search for or filter certain information. With mle we propose a new way to automatically process mailing list archives. The tool is realised based on two Semantic Web technologies: Firstly, SIOC is utilised as the primary vocabulary for describing posts, people, and topics; secondly the RDF metadata is deployed by means of embedding it in the Web page encoded in RDFa.
---
paper_title: Integrating Folksonomies with the Semantic Web

paper_content:

While tags in collaborative tagging systems serve primarily an indexing purpose, facilitating search and navigation of resources, the use of the same tags by more than one individual can yield a collective classification schema. We present an approach for making explicit the semantics behind the tag space in social tagging systems, so that this collaborative organization can emerge in the form of groups of concepts and partial ontologies. This is achieved by using a combination of shallow pre-processing strategies and statistical techniques together with knowledge provided by ontologies available on the semantic web. Preliminary results on the del.icio.us and Flickr tag sets show that the approach is very promising: it generates clusters with highly related tags corresponding to concepts in ontologies and meaningful relationships among subsets of these tags can be identified.
---
paper_title: Ontology of Folksonomy: A Mash-Up of Apples and Oranges

paper_content:

Ontologies are enabling technology for the Semantic Web. They are a means for people to state what they mean by the terms used in data that they might generate, share, or consume. Folksonomies are an emergent phenomenon of the social Web. They arise from data about how people associate terms with content that they generate, share, or consume. Recently the two ideas have been put into opposition, as if they were right and left poles of a political spectrum. This is a false dichotomy; they are more like apples and oranges. In fact, as the Semantic Web matures and the social Web grows, there is increasing value in applying Semantic Web technologies to the data of the social Web. This article is an attempt to clarify the distinct roles for ontologies and folksonomies, and preview some new work that applies the two ideas togetherâ€”an ontology of folk-sonomy.
---
paper_title: The complex dynamics of collaborative tagging

paper_content:

The debate within the Web community over the optimal means by which to organize information often pits formalized classifications against distributed collaborative tagging systems. A number of questions remain unanswered, however, regarding the nature of collaborative tagging systems including whether coherent categorization schemes can emerge from unsupervised tagging by users. This paper uses data from the social bookmarking site delicio. us to examine the dynamics of collaborative tagging systems. In particular, we examine whether the distribution of the frequency of use of tags for "popular" sites with a long history (many tags and many users) can be described by a power law distribution, often characteristic of what are considered complex systems. We produce a generative model of collaborative tagging in order to understand the basic dynamics behind tagging, including how a power law distribution of tags could arise. We empirically examine the tagging history of sites in order to determine how this distribution arises over time and to determine the patterns prior to a stable distribution. Lastly, by focusing on the high-frequency tags of a site where the distribution of tags is a stabilized power law, we show how tag co-occurrence networks for a sample domain of tags can be used to analyze the meaning of particular tags given their relationship to other tags.
---
paper_title: Using Ontologies to Strengthen Folksonomies and Enrich Information Retrieval in Weblogs

paper_content:

While free-tagging classification is widely used in social software implementations and especially in weblogs, it raises various issues regarding information retrieval. In this paper, we describe an approach that mixes folksonomies and semantic web technologies in order to solve some of these problems, and to enrich information retrieval capabilities among blog posts. We first introduce the corporate context of the study and the issues we have faced that motivated our approach. Then, we argue how the use of domain ontologies combined with the SIOC vocabulary on the top of an existing folksonomy and weblogging platform offers a way to get rid of free-tagging classification flaws, and enhances information retrieval by suggesting related blog posts. Aside of the theoretical background, this paper also focuses on implementation. We present experimental results of this approach through the example of add-ons to a corporate blogging platform and the associated semantic web search engine, that extensively uses RDF and other semantic web technologies to find appropriate information and suggest related posts.
---
paper_title: Ontologies are us: a unified model of social networks and semantics

paper_content:

In our work we extend the traditional bipartite model of ontologies with the social dimension, leading to a tripartite model of actors, concepts and instances. We demonstrate the application of this representation by showing how community-based semantics emerges from this model through a process of graph transformation. We illustrate ontology emergence by two case studies, an analysis of a large scale folksonomy system and a novel method for the extraction of community-based ontologies from Web pages.
---
paper_title: Towards Semantically-Interlinked Online Communities

paper_content:

Online community sites have replaced the traditional means of keeping a community informed via libraries and publishing. At present, online communities are islands that are not interlinked. We describe different types of online communities and tools that are currently used to build and support such communities. Ontologies and Semantic Web technologies offer an upgrade path to providing more complex services. Fusing information and inferring links between the various applications and types of information provides relevant insights that make the available information on the Internet more valuable. We present the SIOC ontology which combines terms from vocabularies that already exist with new terms needed to describe the relationships between concepts in the realm of online community sites.
---
paper_title: Integrating Folksonomies with the Semantic Web

paper_content:

While tags in collaborative tagging systems serve primarily an indexing purpose, facilitating search and navigation of resources, the use of the same tags by more than one individual can yield a collective classification schema. We present an approach for making explicit the semantics behind the tag space in social tagging systems, so that this collaborative organization can emerge in the form of groups of concepts and partial ontologies. This is achieved by using a combination of shallow pre-processing strategies and statistical techniques together with knowledge provided by ontologies available on the semantic web. Preliminary results on the del.icio.us and Flickr tag sets show that the approach is very promising: it generates clusters with highly related tags corresponding to concepts in ontologies and meaningful relationships among subsets of these tags can be identified.
---
paper_title: Using Ontologies to Strengthen Folksonomies and Enrich Information Retrieval in Weblogs

paper_content:

While free-tagging classification is widely used in social software implementations and especially in weblogs, it raises various issues regarding information retrieval. In this paper, we describe an approach that mixes folksonomies and semantic web technologies in order to solve some of these problems, and to enrich information retrieval capabilities among blog posts. We first introduce the corporate context of the study and the issues we have faced that motivated our approach. Then, we argue how the use of domain ontologies combined with the SIOC vocabulary on the top of an existing folksonomy and weblogging platform offers a way to get rid of free-tagging classification flaws, and enhances information retrieval by suggesting related blog posts. Aside of the theoretical background, this paper also focuses on implementation. We present experimental results of this approach through the example of add-ons to a corporate blogging platform and the associated semantic web search engine, that extensively uses RDF and other semantic web technologies to find appropriate information and suggest related posts.
---
paper_title: Ontologies are us: a unified model of social networks and semantics

paper_content:

In our work we extend the traditional bipartite model of ontologies with the social dimension, leading to a tripartite model of actors, concepts and instances. We demonstrate the application of this representation by showing how community-based semantics emerges from this model through a process of graph transformation. We illustrate ontology emergence by two case studies, an analysis of a large scale folksonomy system and a novel method for the extraction of community-based ontologies from Web pages.
---
paper_title: Extreme Tagging: Emergent Semantics through the Tagging of Tags

paper_content:

While the Semantic Web requires a large amount of structured knowledge (triples) to allow machine reasoning, the acquisition of this knowledge still represents an open issue. Indeed, expressing expert knowledge in a given formalism is a tedious process. Less structured annotations such as tagging have, however, proved immensely popular, whilst existing unstructured or semi-structured collaborative knowledge bases such as Wikipedia have proven to be useful and scalable. Both processes are often regulated through social mechanisms such as wiki-like operations, recommendations, ratings, and collaborative games. To promote collaborative tagging as a means to acquire unstructured as well as structured knowledge we introduce the notion of Extreme Tagging, which describes systems which allow the tagging of resources, as well as of tags themselves and their relations. We provide a formal description of extreme tagging followed by examples and highlight the necessity of regulatory processes which can be applied to it. We also present a prototype implementation.
---

Title: Bridging Ontologies and Folksonomies to Leverage Knowledge Sharing on the Social Web: A Brief Survey

Section 1: Introduction
Description 1: Introduce the paper's focus on leveraging knowledge sharing through bridging ontologies and folksonomies on the social web.

Section 2: Structure in Folksonomies
Description 2: Discuss the analysis of semantic information within folksonomies and methods to extract semantic relationships.

Section 3: Clustering and Mapping with Ontologies
Description 3: Explain methods for clustering tags and mapping them to ontological concepts.

Section 4: Data Mining and Folksonomies
Description 4: Describe the application of data mining techniques to extract meaningful information from folksonomies.

Section 5: Enriching Folksonomies
Description 5: Present works that support folksonomies with semantic web technologies to enrich social tagging platforms.

Section 6: Guiding Tagging with Ontologies
Description 6: Discuss solutions to integrate ontologies minimally intrusively with social tagging interfaces.

Section 7: Building an Ontology of Folksonomy
Description 7: Describe the construction and benefits of an ontology dedicated to formalizing the act of tagging.

Section 8: Ontologies to Interlink Social Softwares
Description 8: Present contributions aiming to interconnect online communities using semantic web formalisms.

Section 9: Social Aspects
Description 9: Address the social aspects and design models fitting the actual usage of knowledge sharing platforms.

Section 10: Perspectives
Description 10: Provide perspectives on the integration of folksonomies with semantic web technologies, including remaining challenges and future opportunities.