OntoMiner: automated metadata and instance mining from news websites

Davulcu, Hasan; Vadrevu, Srinivas; Nagarajan, Saravanakumar

doi:10.1504/ijwgs.2005.008320

Cited by 5 publications

(3 citation statements)

References 26 publications

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“…Several approaches to semantic annotation of text have been developed, for example, Baumgartner et al [6], Carme et al [29], Ciravegna and Wilks [30], Davulcu et al [31], Euzenat [32], Hanndschuh et al [7], Petridis et al [33], Rahayu [8], Sitthisarn and Bahoh [9] and Uren et al [10]. These approaches are based on natural language processing to extract data categories.…”

Section: Resultsmentioning

confidence: 99%

Generation of Heterogeneous Semantic Annotations of XML Pages: A Multi-viewpoints Approach

Djezzar¹,

Hemam

Ouhiba

et al. 2021

IJCAI

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The semantic annotations presented in current research are based on consensual descriptions of domain knowledge which are used to generate a consensual interpretation of the resource content. Sometimes specialists in a domain want to enrich this interpretation with specific interpretations based on their specialties, consistent with the interpretations of other specialists. However, extant work cannot enrich consensual annotations with heterogeneous annotations. We propose an approach that constructs a consensual (global) annotation and then enriches the consensual annotation with heterogeneous (local) annotations, each of which is a specification of the global annotation. The heterogeneous annotations are consistent with the global interpretations and with one another. What is unique in our approach is that one element in a resource can be annotated with different specific concepts, based on different viewpoints. Our approach utilizes a multi-viewpoints ontology [1], with heterogeneity at the local level and consensus at the global level. Povzetek: Predstavljena je metoda za generiranje heterogenih semantičnih anotacij XML strani na osnovi različnih, a skladnih pogledov

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Section: Resultsmentioning

confidence: 99%

Generation of Heterogeneous Semantic Annotations of XML Pages: A Multi-viewpoints Approach

Djezzar¹,

Hemam

Ouhiba

et al. 2021

IJCAI

View full text Add to dashboard Cite

show abstract

“…Some works are based on supervised approaches or on the existence of structure models in the input documents as in [7], [8], [10] or in text as in [3], [12]. Generally, the assumed hypotheses are incompatible with the heterogeneity and the great number of documents.…”

Section: Introductionmentioning

confidence: 99%

Incremental Ontology-Based Extraction and Alignment in Semi-structured Documents

Thiam

Bennacer

Pernelle

et al. 2009

Lecture Notes in Computer Science

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Abstract. SHIRI1 is an ontology-based system for integration of semistructured documents related to a specific domain. The system's purpose is to allow users to access to relevant parts of documents as answers to their queries. SHIRI uses RDF/OWL for representation of resources and SPARQL for their querying. It relies on an automatic, unsupervised and ontology-driven approach for extraction, alignment and semantic annotation of tagged elements of documents. In this paper, we focus on the Extract-Align algorithm which exploits a set of named entity and term patterns to extract term candidates to be aligned with the ontology. It proceeds in an incremental manner in order to populate the ontology with terms describing instances of the domain and to reduce the access to extern resources such as Web. We experiment it on a HTML corpus related to call for papers in computer science and the results that we obtain are very promising. These results show how the incremental behaviour of Extract-Align algorithm enriches the ontology and the number of terms (or named entities) aligned directly with the ontology increases.

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“…In this paper, we present the METEOR system, which utilizes various presentation and linkage regularities within web pages (Yang et al , 2003b) from referral lists of various sorts to automatically extract meta‐data and instance information. The METEOR system differs from earlier approaches (Davulcu et al , 2003a, b, 2005; Vadrevu et al , 2005a, b) in that it gathers and extracts meta‐data and instance information from object lists on the web; whereas the previous techniques worked with a collection of domain‐specific web sites to mine a domain taxonomy and its instances. The METEOR system is also capable of extracting logical facts from web pages.…”

Section: Introductionmentioning

confidence: 99%

Gathering meta‐data and instances from object referral lists on the web

Vadrevu

Gelgi

Nagarajan

et al. 2006

Online Information Review

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PurposeThe purpose of this research is to automatically separate and extract meta‐data and instance information from various link pages in the web, by utilizing presentation and linkage regularities on the web.Design/methodology/approachResearch objectives have been achieved through an information extraction system called semantic partitioner that automatically organizes the content in each web page into a hierarchical structure, and an algorithm that interprets and translates these hierarchical structures into logical statements by distinguishing and representing the meta‐data and their individual data instances.FindingsExperimental results for the university domain with 12 computer science department web sites, comprising 361 individual faculty and course home pages indicate that the performance of the meta‐data and instance extraction averages 85, 88 percent F‐measure, respectively. Our METEOR system achieves this performance without any domain specific engineering requirement.Originality/valueImportant contributions of the METEOR system presented in this paper are: it performs extraction without the assumption that the object instance pages are template‐driven; it is domain independent and does not require any previously engineered domain ontology; and by interpreting the link pages, it can extract both meta‐data, such as concept and attribute names and their relationships, as well as their instances with high accuracy.

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OntoMiner: automated metadata and instance mining from news websites

Cited by 5 publications

References 26 publications

Generation of Heterogeneous Semantic Annotations of XML Pages: A Multi-viewpoints Approach

Generation of Heterogeneous Semantic Annotations of XML Pages: A Multi-viewpoints Approach

Incremental Ontology-Based Extraction and Alignment in Semi-structured Documents

Gathering meta‐data and instances from object referral lists on the web

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