Mukda Suktarachan

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.

Development of an Information Integration and Knowledge Fusion Platform for Spatial and Time Based Advisory Services: Precision Farming as a Case Study

One of the most challenging knowledge services is to provide information relevant enough to support making effective decisions in real time. Even though many sources of relevant data and knowledge are available on websites at any given time, they are scattered and offer little or no information on the semantic relationships, thus making such sources hard to exploit. This paper proposes an approach to developing a spatial and time-based advisory system by using ontology for aggregating data from heterogeneous databases, and from devices such as climate sensors and mobile phones, using shallow parsing to extract the domain-specific concepts and their attributes from semi-structured text, and using production rules to activate functional knowledge formalized from natural language text that is dispersed across the Web. Precision farming for rice is used as a case study since it relies upon intensive sensing of environmental conditions of the crop, extensive data handling and processing, and farmer knowledge. This work aims to support resource-poor farmers toward higher productivity while minimizing costs. The service offered is to therefore provide personal assistance, thus enhancing a farmers ability to apply actions effectively according to the crop calendar, i.e. the optimal use of pesticides and nutrients in heterogeneous field situations that affect crop quality and reduce risk.

An Application of Lexical Semantics Annotation to Question-Answering in e-Farming

In this poster we present an approach to responding to complex questions in the agriculture domain, from specifications given by experts. We present in particular a semantic annotation procedure that would allow us to define accurate and domain dedicated forms of lexical semantics inference, in order to be able to match non factoid questions (i.e. questions whose response is a significant text portion) with documents on a large scale. This project is designed to help farmers to get advices via question answering on SMS in order to improve rice farming.

The Development of Semi-automatic Sentiment Lexicon Construction Tool for Thai Sentiment Analysis

Sentiment analysis has gained so much interest from many companies and organizations in Thailand. However, there are a few research studies focused on developing Thai sentiment lexicon, which is an important resource for the sentiment analysis. In this work, we developed a web-based automatic Thai lexicon construction tool. Our tool employed a semi-supervised approach for semi-automatically extracting the sentiment lexicon entries. To reduce a negative impact from unreliable parser, we provide simple heuristic rules and mutual information for recognizing sentiment words and its features. The polarity of recognized sentiment words is automatically identified through a bootstrapping process that utilizes a small set of sentiment seeds, the context coherency characteristics, and statistical co-occurrence. In the evaluation, we received quite fair results for lexicon construction task, 76.06 and 75.28 F-Score for hotel review and laptop review, respectively.

From CyberBrain to Q&A Services: A Development of Question-Answering Services System for the Farmer through the SMS

The Question-Answering Services System proposed in this article is designed to help farmers to get advices on SMS. It operates on top of search engines or on classical textual database querying tools by providing a layer that has natural language understanding and generation functions as well as some reasoning capabilities in order to provide users with responses. This is particularly crucial when there is no straightforward response. In this paper, we show how annotation guidelines can be developed to model the semantics of “What”, “Why” and “How” queries and “Answer” in texts based on semantic roles. Finally, we show how these annotations and inference rule contribute to the generalization of the matching system over semantic categories in order to have a large scale question-answering system.

A multilingual analysis of the notion of instrumentality

Instruments are expressed in language by various means: prepositions, postpositions, affixes including case marks, nonfinite verbs, etc. We consider here 12 languages from five families in order to be able to identify the different meaning components that structure instrumentality.