OntoMiner: bootstrapping and populating ontologies from domain-specific Web sites

Davalcu, H.; Vadrevu, Srinivas; Nagarajan, Saravanakumar; Ramakrishnan, I. V.

doi:10.1109/mis.2003.1234766

Cited by 69 publications

(46 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…An RDF is a widely recognized standard for annotating online Web documents and for transforming the HTML Web to the Semantic Web (Davalcu, et al 2003). RDF was specified by the WWW Consortium (W3C) and was originally designed as a metadata model so that it provides a syntax convention for representing the semantic of data in a standardized interoperable manner.…”

Section: Semantic Web: Building Blocksmentioning

confidence: 99%

Role of Semantic Web in the Changing Context of Enterprise Collaboration

Khilwani

2013

Interoperability for Enterprise Software and Applications

View full text Add to dashboard Cite

Section: Semantic Web: Building Blocksmentioning

confidence: 99%

Role of Semantic Web in the Changing Context of Enterprise Collaboration

Khilwani

2013

Interoperability for Enterprise Software and Applications

View full text Add to dashboard Cite

“…OntoBuilder [16] also constructs a taxonomy of concepts by parsing Web search forms, although the authors do not describe the algorithm or the resulting taxonomy in detail. OntoMiner [17] learns a taxonomy of concepts from co-domain Web sites. It relies on HTML regularities to construct taxonomic structures in XML by utilizing a hierarchical partition algorithm.…”

Section: Rdf Data Extractionmentioning

confidence: 99%

An Unsupervised Approach for Acquiring Ontologies and RDF Data from Online Life Science Databases

Mir

Staab

Rojas

2010

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. In the Linked Open Data cloud one of the largest data sets, comprising of 2.5 billion triples, is derived from the Life Science domain. Yet this represents a small fraction of the total number of publicly available data sources on the Web. We briefly describe past attempts to transform specific Life Science sources from a plethora of open as well as proprietary formats into RDF data. In particular, we identify and tackle two bottlenecks in current practice: Acquiring ontologies to formally describe these data and creating "RDFizer" programs to convert data from legacy formats into RDF. We propose an unsupervised method, based on transformation rules, for performing these two key tasks, which makes use of our previous work on unsupervised wrapper induction for extracting labelled data from complete Life Science Web sites. We apply our approach to 13 real-world online Life Science databases. The learned ontologies are evaluated by domain experts as well as against gold standard ontologies. Furthermore, we compare the learned ontologies against ontologies that are "lifted" directly from the underlying relational schema using an existing unsupervised approach. Finally, we apply our approach to three online databases to extract RDF data. Our results indicate that this approach can be used to bootstrap and speed up the migration of life science data into the Linked Open Data cloud.

show abstract

“…OntoMiner [5,6] is an unsupervised system which leverages the HTML regularities in the Web documents to detect key-concepts and bootstrapping and populating specialized domain ontologies by organizing and mining taxonomy-directed Web sites.…”

Section: Related Workmentioning

confidence: 99%

Using tagflake for condensing navigable tag hierarchies from tag clouds

Di¹,

Candan

Sapino³

2008

Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

View full text Add to dashboard Cite

We present the tagFlake system, which supports semantically informed navigation within a tag cloud. tagFlake relies on TMine for organizing tags extracted from textual content in hierarchical organizations, suitable for navigation, visualization, classification, and tracking. TMine extracts the most significant tag/terms from text documents and maps them onto a hierarchy in such a way that descendant terms are contextually dependent on their ancestors within the given corpus of documents. This provides tagFlake with a mechanism for enabling navigation within the tag space and for classification of the text documents based on the contextual structure captured by the created hierarchy. tagFlake is language neutral, since it does not rely on any natural language processing technique and is unsupervised. Categories and Subject Descriptors General TermsAlgorithms, Human Factors MOTIVATIONWith the quick growth of content over the web (e.g., the blogosphere), tag-based searches and tag cloud (sets of tags) based visualizations have become popular. Tags, whether provided by the user or extracted from the textual content, annotate online documents (such as blogs and news articles) with popular terms, thus providing an easy way to search and index them.Most visualizations of tag clouds vary the sizes of the fonts to differentiate most important tags from those that are less important (Figure 1). [2] aims creating visually pleasant tag clouds, by presenting tags in the form of seemingly random collections of circles with varying sizes: the size of the circle denotes its frequency. While quickly highlighting the most dominant terms in the corpus, these representations fall short in describing the context in which these terms occur in the collection. * This work is partially supported by NSF Award #0735014,"MAISON: Middleware for Accessible Information Spaces on NSDL". The need for contextually informed navigation within the blogosphere has been highlighted in the literature. For example, [16] observes that for large blog archives, a simple chronological order is not sufficient and a table of contents (TOC) like navigational hierarchy, depicting the topics development within the blog archive and describing how these topics relate to each other would be more effective.

show abstract

OntoMiner: bootstrapping and populating ontologies from domain-specific Web sites

Cited by 69 publications

References 15 publications

Role of Semantic Web in the Changing Context of Enterprise Collaboration

Role of Semantic Web in the Changing Context of Enterprise Collaboration

An Unsupervised Approach for Acquiring Ontologies and RDF Data from Online Life Science Databases

Using tagflake for condensing navigable tag hierarchies from tag clouds

Contact Info

Product

Resources

About