Omnibase: Uniform Access to Heterogeneous Data for Question Answering

Katz, Boris; Felshin, Sue; Yüret, Deniz; Ibrahim, Ali; Lin, Jimmy; Marton, Gregory; McFarland, Alton Jerome; Temelkuran, Baris

doi:10.1007/3-540-36271-1_23

Cited by 66 publications

(49 citation statements)

References 7 publications

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“…The START [33] system goal is also to extract answers from text. AquaLog relational data model (triple-based) is somehow similar to the approach adopted by START, called "object-property-value".…”

Section: Open-domain Qa Systems Using Triple Representationmentioning

confidence: 99%

AquaLog: An Ontology-Portable Question Answering System for the Semantic Web

López

Pasin

Motta

2005

Lecture Notes in Computer Science

148

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Abstract. As semantic markup becomes ubiquitous, it will become important to be able to ask queries and obtain answers, using natural language (NL) expressions, rather than the keyword-based retrieval mechanisms used by the current search engines. AquaLog is a portable question-answering system which takes queries expressed in natural language and an ontology as input and returns answers drawn from the available semantic markup. We say that AquaLog is portable, because the configuration time required to customize the system for a particular ontology is negligible. AquaLog combines several powerful techniques in a novel way to make sense of NL queries and to map them to semantic markup. Moreover it also includes a learning component, which ensures that the performance of the system improves over time, in response to the particular community jargon used by the end users. In this paper we describe the current version of the system, in particular discussing its portability, its reasoning capabilities, and its learning mechanism.

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Section: Open-domain Qa Systems Using Triple Representationmentioning

confidence: 99%

AquaLog: An Ontology-Portable Question Answering System for the Semantic Web

López

Pasin

Motta

2005

Lecture Notes in Computer Science

148

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“…The internet technology makes strong support to advance open-domain question answering systems in contrast to closed domain systems. The pioneer in such open-domain question answering system named as START [15,16]. The method developed in and around 1992 for answering natural language questions by giving textual extracts and multimedia info mined from the World Wide Web Internet.…”

Section: Related Workmentioning

confidence: 99%

Cognitive Functionality based Question Answering System

Chandiok¹,

Chaturvedi²

2018

IJCA

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Applying cognitive functionality in the artificial system is the prospect of next computing era and is speedily attracting the business and industry. As the volume of information increasing rapidly in the digital world, it also tends to challenge the current search engines to mine more significant and related information in precise and comprehensible manner. A Question Answering (QA) system outdoes the traditional information retrieval search engines in such situations. The paper presents and implements cognitive functionality in question answering systems to mimic human-like performance. The work proposes an architecture which trails human mental and brain like problemsolving procedures to answer questions. An illustration also deliberated and elucidated using a practical implementation and evaluation along with its fundamental cognitive functionality.

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“…Natural language search engines such as AskJeeves [27] and EasyAsk [28] exist, as well as systems such as START [13] and REXTOR [21], whose goal is to extract answers from text. AnswerBus [29] is another open-domain question-answering system based on web information retrieval.…”

Section: Related Workmentioning

confidence: 99%

Ontology-Driven Question Answering in AquaLog

López

Motta

2004

Lecture Notes in Computer Science

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The semantic web vision is one in which rich, ontology-based semantic markup is widely available, both to enable sophisticated interoperability among agents and to support human web users in locating and making sense of information. The availability of semantic markup on the web also opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system which takes queries expressed in natural language and an ontology as input and returns answers drawn from one or more knowledge bases (KBs), which instantiate the input ontology with domain-specific information. AquaLog makes use of the GATE NLP platform, string metrics algorithms, WordNet and a novel ontology-based relation similarity service to make sense of user queries with respect to the target knowledge base. Finally, although AquaLog has primarily been designed for use with semantic web languages, it makes use of a generic plug-in mechanism, which means it can be easily interfaced to different ontology servers and knowledge representation platforms.

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Omnibase: Uniform Access to Heterogeneous Data for Question Answering

Cited by 66 publications

References 7 publications

AquaLog: An Ontology-Portable Question Answering System for the Semantic Web

AquaLog: An Ontology-Portable Question Answering System for the Semantic Web

Cognitive Functionality based Question Answering System

Ontology-Driven Question Answering in AquaLog

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