"All You Can Eat" Ontology-Building: Feeding Wikipedia to Cyc

Sarjant, Samuel; Legg, Catherine; Robinson, Michael; Medelyan, Olena

doi:10.1109/wi-iat.2009.60

Cited by 19 publications

(10 citation statements)

References 8 publications

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“…Wikipedia has also been exploited for ontology construction [19]. In particular, the multi-faceted categorization and cross-references of concepts in Wikipedia provide researchers with information necessary to automatically construct domainspecific and general-purpose ontologies [20].…”

Section: Wikipedia As a Text Corpusmentioning

confidence: 99%

Exploiting online human knowledge in Requirements Engineering

Mahmoud

Carver

2015

2015 IEEE 23rd International Requirements Engineering Conference (RE)

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Data-driven Natural Language Processing (NLP) methods have noticeably advanced in the past few years. These advances can be tied to the drastic growth of the quality of collaborative knowledge bases (KB) available on the World Wide Web. Such KBs contain vast amounts of up-to-date structured human knowledge and common sense data that can be exploited by NLP methods to discover otherwise-unseen semantic dimensions in text, aiding in tasks related to natural language understanding, classification, and retrieval. Motivated by these observations, we describe our research agenda for exploiting online human knowledge in Requirements Engineering (RE). The underlying assumption is that requirements are a product of the human domain knowledge that is expressed mainly in natural language. In particular, our research is focused on methods that exploit the online encyclopedia Wikipedia as a textual corpus. Wikipedia provides access to a massive number of real-world concepts organized in hierarchical semantic structures. Such knowledge can be analyzed to provide automated support for several exhaustive RE activities including requirements elicitation, understanding, modeling, traceability, and reuse, across multiple application domains. This paper describes our preliminary findings in this domain, current state of research, and prospects of our future work.

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Section: Wikipedia As a Text Corpusmentioning

confidence: 99%

Exploiting online human knowledge in Requirements Engineering

Mahmoud

Carver

2015

2015 IEEE 23rd International Requirements Engineering Conference (RE)

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“…Extracted taxonomies are an intermediate step in constructing larger and more expressive knowledge structures, or in enlarging existing ones. 48,49 Evaluating hierarchies is a difficult task, and quality can rarely be captured by a single metric. Some researchers compare the hierarchy they produce to existing ones in terms of coverage 48 or in terms of its ability to support particular tasks.…”

Section: From Terms To Hierarchiesmentioning

confidence: 99%

“…50 Others recruit human judges to estimate the quality of a hierarchy, either overall or in terms of particular relations. 46,49…”

Section: From Terms To Hierarchiesmentioning

confidence: 99%

Automatic construction of lexicons, taxonomies, ontologies, and other knowledge structures

Medelyan¹,

Witten

Divoli³

et al. 2013

WIREs Data Min & Knowl

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structured, representations of knowledge such as lexicons, taxonomies, and ontologies have proven to be powerful resources not only for the systematization of knowledge in general, but to support practical technologies of document organization, information retrieval, natural language understanding, and question-answering systems. These resources are extremely time consuming for people to create and maintain, yet demand for them is growing, particularly in specialized areas ranging from legacy documents of large enterprises to rapidly changing domains such as current affairs and celebrity news. Consequently, researchers are investigating methods of creating such structures automatically from document collections, calling on the proliferation of interlinked resources already available on the web for background knowledge and general information about the world. This review surveys what is possible, and also outlines current research directions. C 2013 Wiley Periodicals, Inc.

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“…De Silva and Jayaratne [22] introduced WikiOnto which extract and model ontology from Wikipedia XML corpus using Natural Language Processing (NLP) and machine learning techniques. WikiOnto composed of three phases, in the first phase concepts and candidate relationships (sub-conceptOf) with each other were extracted using the provided XML document structure.…”

Section: Ontology Buildingmentioning

confidence: 99%

Semantic Relationship Extraction and Ontology Building using Wikipedia: A Comprehensive Survey

Rajebah¹,

Al‐Khalifa²

2010

IJCA

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Semantic web as a vision of Tim Berners-Lee is highly dependable upon the availability of machine readable information. Ontologies are one of the different machine readable formats that have been widely investigated. Several studies focus on how to extract concepts and semantic relations in order to build ontologies. Wikipedia is considered as one of the important knowledge sources that have been used to extract semantic relations due to its characteristics as a semi-structured knowledge source that would facilitate such a challenge. In this paper we will focus on the current state of this challenging field by discussing some of the recent studies about Wikipedia and semantic extraction and highlighting their main contributions and results.

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"All You Can Eat" Ontology-Building: Feeding Wikipedia to Cyc

Cited by 19 publications

References 8 publications

Exploiting online human knowledge in Requirements Engineering

Exploiting online human knowledge in Requirements Engineering

Automatic construction of lexicons, taxonomies, ontologies, and other knowledge structures

Semantic Relationship Extraction and Ontology Building using Wikipedia: A Comprehensive Survey

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