Building Knowledge Management System for Researching Terrorist Groups on the Web

Nowadays, terrorist organizations have found a cost-effective resource to advance their courses by posting high-impact Web sites on the Internet. This alternate side of the Web is referred to as the “Dark Web.” While counterterrorism researchers seek to obtain and analyze information from the Dark Web, several problems prevent effective and efficient knowledge discovery: the dynamic and hidden character of terrorist Web sites, information overload, and language barrier problems. This study proposes an intelligent knowledge management system to support the discovery and analysis of multilingual terrorist-created Web data. We developed a systematic approach to identify, collect and store up-to-date multilingual terrorist Web data. We also propose to build an intelligent Web-based knowledge portal integrated with advanced text and Web mining techniques such as summarization, categorization and cross-lingual retrieval to facilitate the knowledge discovery from Dark Web resources. We believe our knowledge portal provide counterterrorism research communities with valuable datasets and tools in knowledge discovery and sharing

Introduction to the special issue on cross-language algorithms and applications

With the increasingly global nature of our everyday interactions, the need for multilingual technologies to support efficient and efective information access and communication cannot be overemphasized. Computational modeling of language has been the focus of Natural Language Processing, a subdiscipline of Artificial Intelligence. One of the current challenges for this discipline is to design methodologies and algorithms that are cross-language in order to create multilingual technologies rapidly. The goal of this JAIR special issue on Cross-Language Algorithms and Applications (CLAA) is to present leading research in this area, with emphasis on developing unifying themes that could lead to the development of the science of multi- and cross-lingualism. In this introduction, we provide the reader with the motivation for this special issue and summarize the contributions of the papers that have been included. The selected papers cover a broad range of cross-lingual technologies including machine translation, domain and language adaptation for sentiment analysis, cross-language lexical resources, dependency parsing, information retrieval and knowledge representation. We anticipate that this special issue will serve as an invaluable resource for researchers interested in topics of cross-lingual natural language processing.Postprint (published version

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

Information Access in a Multilingual World: Transitioning from Research to Real-World Applications

Multilingual Information Access (MLIA) is at a turning point wherein substantial real-world applications are being introduced after fifteen years of research into cross-language information retrieval, question answering, statistical machine translation and named entity recognition. Previous workshops on this topic have focused on research and small- scale applications. The focus of this workshop was on technology transfer from research to applications and on what future research needs to be done which facilitates MLIA in an increasingly connected multilingual world