ANNIS: a linguistic database for exploring information structure

In this paper, we discuss the design and implementation of our first version of the database "ANNIS" (ANNotation of Information Structure). For research based on empirical data, ANNIS provides a uniform environment for storing this data together with its linguistic annotations. A central database promotes standardized annotation, which facilitates interpretation and comparison of the data. ANNIS is used through a standard web browser and offers tier-based visualization of data and annotations, as well as search facilities that allow for cross-level and cross-sentential queries. The paper motivates the design of the system, characterizes its user interface, and provides an initial technical evaluation of ANNIS with respect to data size and query processing

PowerAqua: fishing the semantic web

The Semantic Web (SW) offers an opportunity to develop novel, sophisticated forms of question answering (QA). Specifically, the availability of distributed semantic markup on a large scale opens the way to QA systems which can make use of such semantic information to provide precise, formally derived answers to questions. At the same time the distributed, heterogeneous, large-scale nature of the semantic information introduces significant challenges. In this paper we describe the design of a QA system, PowerAqua, designed to exploit semantic markup on the web to provide answers to questions posed in natural language. PowerAqua does not assume that the user has any prior information about the semantic resources. The system takes as input a natural language query, translates it into a set of logical queries, which are then answered by consulting and aggregating information derived from multiple heterogeneous semantic sources

Multimedia search without visual analysis: the value of linguistic and contextual information

This paper addresses the focus of this special issue by analyzing the potential contribution of linguistic content and other non-image aspects to the processing of audiovisual data. It summarizes the various ways in which linguistic content analysis contributes to enhancing the semantic annotation of multimedia content, and, as a consequence, to improving the effectiveness of conceptual media access tools. A number of techniques are presented, including the time-alignment of textual resources, audio and speech processing, content reduction and reasoning tools, and the exploitation of surface features

Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

Knowledge Engineering in Search Engines

With large amounts of information being exchanged on the Internet, search engines have become the most popular tools for helping users to search and filter this information. However, keyword-based search engines sometimes obtain information, which does not meet user’ needs. Some of them are even irrelevant to what the user queries. When the users get query results, they have to read and organize them by themselves. It is not easy for users to handle information when a search engine returns several million results. This project uses a granular computing approach to find knowledge structures of a search engine. The project focuses on knowledge engineering components of a search engine. Based on the earlier work of Dr. Lin and his former student [1], it represents concepts in the Web by simplicial complexes. We found that to represent simplicial complexes adequately, we only need the maximal simplexes. Therefore, this project focuses on building maximal simplexes. Since it is too costly to analyze all Web pages or documents, the project uses the sampling method to get sampling documents. The project constructs simplexes of documents and uses the simplexes to find maximal simplexes. These maximal simplexes are regarded as primitive concepts that can represent Web pages or documents. The maximal simplexes can be used to build an index of a search engine in the future