Aqualog: An ontology-portable question answering system for the semantic web (original) (raw)

AquaLog A Ontology-portable Question Answering interface for the Semantic Web

2005

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.

AquaLog: An ontology-driven question answering system to interface the semantic web

2006

Abstract The semantic web (SW) vision is one in which rich, ontology-based semantic markup will become widely available. The availability of semantic markup on the web opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system which takes queries expressed in natural language (NL) and an ontology as input, and returns answers drawn from one or more knowledge bases (KB).

Ontology-Driven Question Answering in AquaLog

2004

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.

AquaLog: An ontology-driven question answering system for organizational semantic intranets

Journal of Web Semantics, 2007

The semantic web vision is one in which rich, ontology-based semantic markup will become widely available. The availability of semantic markup on the web 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). We say that AquaLog is portable because the configuration time required to customize the system for a particular ontology is negligible. AquaLog presents an elegant solution in which different strategies are combined together in a novel way. It makes use of the GATE NLP platform, string metric algorithms, WordNet and a novel ontology-based relation similarity service to make sense of user queries with respect to the target KB. Moreover it also includes a learning component, which ensures that the performance of the system improves over the time, in response to the particular community jargon used by end users.

AQUA–ontology-based question answering system

2004

This paper describes AQUA, an experimental question answering system. AQUA combines Natural Language Processing (NLP), Ontologies, Logic, and Information Retrieval technologies in a uniform framework. AQUA makes intensive use of an ontology in several parts of the question answering system. The ontology is used in the refinement of the initial query, the reasoning process, and in the novel similarity algorithm. The similarity algorithm, is a key feature of AQUA.

AQUA: A Knowledge-Based Architecture for a Question Answering System

Abstract This paper describes AQUA, a question answering system. AQUA combines Natural Language processing (NLP), Ontologies, Logic, and Information Retrieval technologies in a uniform framework. AQUA makes intensive use of an ontology (which encode knowledge) in several parts of the question answering system.

Query answering systems in the semantic web

2004

Abstract In this paper a new query answering system is presented for querying knowledge bases in the Semantic Web. The implementation follows the DAML+ OIL Query Language Abstract Specification (DQL) and supports acyclic conjunctive queries. The system uses a Description Logic (DL) reasoner to answer the queries and the conjunctive queries are transformed into DL retrieval or boolean queries. After the introduction to the new DQL implementation, a comparison with other systems follows.

QASYO: A Question Answering System for YAGO Ontology

The tremendous development in information technology led to an explosion of data and motivated the need for powerful yet efficient strategies for data mining and knowledge discovery. Question Answering (QA) systems made it possible to ask questions and retrieve answers using natural language (NL) queries, rather than the keyword-based retrieval mechanisms used by current search engines. In Ontology-based QA system, the knowledge based data, where the answers are sought, has a structured organization. The question-answer retrieval of ontology knowledge base provides a convenient way to obtain knowledge for use, but the natural language need to be mapped to the query statement of ontology. QASYO is a sentence level question-answering system that integrates natural language processing, ontologies and information retrieval technologies in a unified framework. It accepts queries expressed in natural language and YAGO ontology as inputs and provides answers drawn from the available semantic markup. QASYO combines several powerful techniques in a novel way to make sense of NL queries and to map them to semantic markup. Semantic analysis of questions is performed in order to extract keywords used in the retrieval queries and to detect the expected answer type. In this paper we describe the current version of the system, in particular discussing its reasoning capabilities, and Performance.

Puzzle Out the Semantic Web Search

2012

The increase in web popularity has created the demand for systems that help the users find relevant information easily. Question Answering systems made it possible to ask questions and retrieve answers using natural language queries, rather than the keywordbased retrieval mechanisms used by current search engines. In this paper we propose a Cooperative Question Answering System that integrates natural language processing, ontologies and information retrieval technologies in a unified framework. It accepts natural language queries and is able to return a cooperative answer based on semantic web resources. Our system resorts to ontologies not only for reasoning but also to find answers and is independent of prior knowledge of the semantic resources by the user. The natural language question is translated into its semantic representation and then answered by consulting the semantics sources of information. The system is able to clarify the problems of ambiguity and helps finding the pa...

Knowledge Baesd Question Answering System Using Ontology

In the modern era numerous information available in the World Wide Web. Question Answering systems aims to retrieve point-to-point answers rather than flooding with documents. It is needed when the user gets an in depth knowledge in a particular domain. When user needs some information, it must give the relevant answer. The basic idea of QA systems in Natural Language Processing (NLP) is to provide correct answers to the questions for the user. Here the question answering system has to be implemented as semantic web. This research will evaluate the answering system by the expert. The experts are personalized based on their domain and subject. Ontology is used to personalize the experts. Based on these, the answer has to be ranked and given back to the user. It consists of three phases such as User’s zone, Interface and Expert’s zone. Natural language processing techniques are used for processing the question and also for answer extraction. The domain knowledge is used for reformulating queries and identifying the relations.The highlight of this paper is providing most relative answer for the question provided by the end users in an efficient way.