Asanee Kawtrakul

BioCaster: detecting public health rumors with a Web-based text mining system

Summary: BioCaster is an ontology-based text mining system for detecting and tracking the distribution of infectious disease outbreaks from linguistic signals on the Web. The system continuously analyzes documents reported from over 1700 RSS feeds, classifies them for topical relevance and plots them onto a Google map using geocoded information. The background knowledge for bridging the gap between Laymans terms and formal-coding systems is contained in the freely available BioCaster ontology which includes information in eight languages focused on the epidemiological role of pathogens as well as geographical locations with their latitudes/longitudes. The system consists of four main stages: topic classification, named entity recognition (NER), disease/location detection and event recognition. Higher order event analysis is used to detect more precisely specified warning signals that can then be notified to registered users via email alerts. Evaluation of the system for topic recognition and entity identification is conducted on a gold standard corpus of annotated news articles. Availability: The BioCaster map and ontology are freely available via a web portal at http://www.biocaster.org. Contact: collier@nii.ac.jp

A multilingual ontology for infectious disease surveillance: rationale, design and challenges

A lack of surveillance system infrastructure in the Asia-Pacific region is seen as hindering the global control of rapidly spreading infectious diseases such as the recent avian H5N1 epidemic. As part of improving surveillance in the region, the BioCaster project aims to develop a system based on text mining for automatically monitoring Internet news and other online sources in several regional languages. At the heart of the system is an application ontology which serves the dual purpose of enabling advanced searches on the mined facts and of allowing the system to make intelligent inferences for assessing the priority of events. However, it became clear early on in the project that existing classification schemes did not have the necessary language coverage or semantic specificity for our needs. In this article we present an overview of our needs and explore in detail the rationale and methods for developing a new conceptual structure and multilingual terminological resource that focusses on priority pathogens and the diseases they cause. The ontology is made freely available as an online database and downloadable OWL file.

Ontology Engineering and Knowledge Services for Agriculture Domain

Abstract This paper presents a knowledge service system for the domain of agriculture. Three key issues for providing knowledge services are how to improve the access of unstructured and scattered information for the non-specialist users, how to provide adequate information to knowledge workers and how to provide the information requiring highly focused and related information. Cyber-Brain has been designed as a platform that combines approaches based on knowledge engineering and language engineering to gather knowledge from various sources and to provide the effective knowledge service. Based on specially designed ontology for practical service scenarios, it can aggregate knowledge from Internet, digital archives, expert, and other resources for providing one-stop-shop knowledge services. The domain specific and task oriented ontology also enables advanced search and allows the system ensures that knowledge service could improve the user benefit. Users are presented with the necessary information closely related to their information need and thus of potential high interest. This paper presents several service scenarios for different end-users and reviews ontology engineering and its life cycle for supporting AOS (Agricultural Ontology Services) Vocbench which is the heart of knowledge services in agriculture domain.

Backward transliteration for Thai document retrieval

Thai text retrieval systems always involve documents that use loan words (borrowed from foreign language), especially in the area of science and engineering. This paper describes an algorithmic approach to backward machine transliteration aimed at improving the retrieval process. The approach consists of two main steps: identifying loan words and back transliterating. The model of backward transliteration works successfully at approximately 95% including phonetic equivalent.

Enabling Future Education with Smart Services

The future of the education system will restructure through information communication technology (ICT), which is a comprehensive approach to innovate education systems, methods, and management. The new paradigm of ICT in educations is smart services, which enhances the education efficiency, effectiveness, and productivity. The education smart services in Thailand, called NEdNet (National Education Network), are integrated systems including network infrastructure services, education information services (EIS), and Learning services, which facilitator of higher-order thinking skills, support learner-centered, self-directed learning, tailored learning and decision supporting. The first part of NEdNet is network infrastructure systems. Ministry of Education proposed National Education Network (NEdNet) project to develop national education network and provide enough bandwidth for all levels of education. NEdNet is the integration of UniNet Network [6] for higher education, MOENet for schools and VECNet for vocational institutes. NEdNet supports usage of the entire education system with the following bandwidth 1) 293 university connected by dark fiber, which will have bandwidth 1-10 Gbps, 2) 415 vocational institutions, which will have bandwidth 100-1,000 Mbps, and finally 3,000 schools, which will have bandwidth 10-100 Mbps. NEdNet also investigates the coming technology such as 3G, WiMax and FTTx for last mile access networks. NEdNet provides either community internet or research education network (REN), which connected to Internet2 in USA., JGN2 in Japan, TEIN (Trans Eurasia Information Network) and APAN (Asia Pacific Advanced Network). The second part of the NEdNet is education information services (EIS) using Service Oriented Architecture (SOA) infrastructure, which provides information for management and executives in three levels. The first level is national level, which establishes a comprehensive e-government project using TH e-Gif (Thailand e-Government Interoperability Framework) [1] to enhance efficiency and quality of general services such as procurement, service delivery, monitoring and evaluation and etc. The second is local level, which shares data and information among education administration organizations and other government departments. The last is school level, which handles education administration in a more efficient, convenient, and innovative way. The last part of NEdNet is Learning services, which provides cloud computing facilities for cyber learning system, digital library (ThaiLis) and educational broadcasting services called E-TV and Teacher TV (IP-TV). These services provide education resources for economically and geographically disadvantaged students and Thailand Cyber University (TCU) for adults to promote lifelong learning. In conclusion, NEdNet is the education smart services, which can contribute to learning outcomes of traditional curriculum domains and can play a greater role in the future education. The network infrastructure decreases students digital-divided in Internet and research networks. The other services are more relevant to quality of education resources, extending learning beyond classrooms, student-centered learning and national competitiveness.

A Semantic Web Framework to Support Knowledge Management in Chronic Disease Healthcare

Improving quality of healthcare for people with chronic conditions requires informed and knowledgeable healthcare providers and patients. Decision support and clinical information system are two of the main components to support improving chronic care. In this paper, we describe an ongoing initiative that emphasizes the need for healthcare knowledge management to support both components. Ontology-based knowledge acquisition and modeling based on knowledge engineering approach provides an effective mechanism in capturing expert opinion in form of clinical practice guidelines. The Semantic Web framework is adopted in building a knowledge management platform that allows integration between the knowledge with patient databases and supported publications. We discuss one of the challenges, which is to apply the healthcare knowledge into existing healthcare provider environments by focusing on augmenting decision making and improving quality of patient care services.

Automatic building of an ontology on the basis of text corpora in Thai

This paper presents a methodology for automatic learning of ontologies from Thai text corpora, by extraction of terms and relations. A shallow parser is used to chunk texts on which we identify taxonomic relations with the help of cues: lexico-syntactic patterns and item lists. The main advantage of the approach is that it simplify the task of concept and relation labeling since cues help for identifying the ontological concept and hinting their relation. However, these techniques pose certain problems, i.e. cue word ambiguity, item list identification, and numerous candidate terms. We also propose the methodology to solve these problems by using lexicon and co-occurrence features and weighting them with information gain. The precision, recall and F-measure of the system are 0.74, 0.78 and 0.76, respectively.

AgriVillage: 3D multi-language internet game for fostering agriculture environmental awareness

Agriculture has a strong impact in the environment; it has played key role in the development of food security and food safety. In this paper, we are proposing a 3D multilingual Internet game, developed by using the on-line virtual world platform, that lets the player experience the potential effects of agriculture in the environment. The main idea is to foster awareness of agricultures environmental issues, by not only making the player learn the impact of fertilizers and deforestation that affect the sources of water and weather, respectively, but also enhance the importance of food quality. To make players care for these issues, the game creates a direct impact by using the happiness of people that is represent by the villagers. To reduce the language barrier when sharing knowledge across the countries is needed, the game also supports multi-language to make it more understandable to the player. This paper describes details of the game design, the system architecture and the experiment. The experiment conducted with the game showed promising results.

A state of the art of Thai Language resources and Thai Language behavior analysis and modeling

As electronic communications is now increasing, the term Natural Language Processing should be considered in the broader aspect of Multi-Language processing system. Observation of the language behavior will provide a good basis for design of computational language model and also creating cost-effective solutions to the practical problems. In order to have a good language modeling, the language resources are necessary for the language behavior analysis.This paper intended to express what we have and what we have done by the desire to make a bridge between the languages and to share and make maximal use of the existing lexica, corpus and the tools. Three main topics are, then, focussed: A State of the Art of Thai language Resources, Thai language behaviors and their computational models.

A framework of NLP based information tracking and related knowledge organizing with topic maps

This paper presents a computational framework for information extraction and aggregation which aims to integrate and organize the data/information resources that spread throughout the Internet in the manner that makes them useful for tracking events such as natural disaster, and disease dispersion. We introduce a simple statistical information extraction technique for summarizing the document into a predefined structure. We apply the topic maps approach as a semantic layer in aggregating and organizing the extracted information for smart access. In addition, this paper also carries out a case study on disease dispersion domain using the proposed framework.