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

Aqualog: An ontology-portable question answering system 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.

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.

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.

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.

Architecture of an Ontology-Based Domain-Specific Natural Language Question Answering System

International journal of Web & Semantic Technology, 2013

Question answering (QA) system aims at retrieving precise information from a large collection of documents against a query. This paper describes the architecture of a Natural Language Question Answering (NLQA) system for a specific domain based on the ontological information, a step towards semantic web question answering. The proposed architecture defines four basic modules suitable for enhancing current QA capabilities with the ability of processing complex questions. The first module was the question processing, which analyses and classifies the question and also reformulates the user query. The second module allows the process of retrieving the relevant documents. The next module processes the retrieved documents, and the last module performs the extraction and generation of a response. Natural language processing techniques are used for processing the question and documents and also for answer extraction. Ontology and domain knowledge are used for reformulating queries and identifying the relations. The aim of the system is to generate short and specific answer to the question that is asked in the natural language in a specific domain. We have achieved 94 % accuracy of natural language question answering in our implementation.

Ontology-based Question Answering System

Data and Information requirement is increasing with the Increase in the volumes of data in the repositories such as www etc, now question arises that out of this enormous data how to find the information which is required by the user and should be specific in nature. Information retrieval techniques solves the problem to an extent but they cannot help in a situation where only specific information pertaining to a question is required. Information retrieval engines will retrieve documents containing phrases and paragraphs which may have an answer to user query. This problem is addressed in this research paper which proposes a question answering system to satisfy users specific information need.

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.

Using ontology in query answering systems: Scenarios, requirements and challenges

2003

Abstract. Equipped with the ultimate query answering system, computers would finally be in a position to address all our information needs in a natural way. In this paper, we describe how Language and Computing nv (L&C), a developer of ontology-based natural language understanding systems for the healthcare domain, is working towards the ultimate Question Answering (QA) System for healthcare workers.