Charnyote Pluempitiwiriyawej

An Internet-based negotiation server for e-commerce

Abstract. This paper describes the design and implementation of a replicable, Internet-based negotiation server for conducting bargaining-type negotiations between enterprises involved in e-commerce and e-business. Enterprises can be buyers and sellers of products/services or participants of a complex supply chain engaged in purchasing, planning, and scheduling. Multiple copies of our server can be installed to complement the services of Web servers. Each enterprise can install or select a trusted negotiation server to represent his/her interests. Web-based GUI tools are used during the build-time registration process to specify the requirements, constraints, and rules that represent negotiation policies and strategies, preference scoring of different data conditions, and aggregation methods for deriving a global cost-benefit score for the item(s) under negotiation. The registration information is used by the negotiation servers to automatically conduct bargaining type negotiations on behalf of their clients. In this paper, we present the architecture of our implementation as well as a framework for automated negotiations, and describe a number of communication primitives which are used in the underlying negotiation protocol. A constraint satisfaction processor (CSP) is used to evaluate a negotiation proposal or counterproposal against the registered requirements and constraints of a client company. In case of a constraint violation, an event is posted to trigger the execution of negotiation strategic rules, which either automatically relax the violated constraint, ask for human intervention, invoke an application, or perform other remedial operations. An Event-Trigger-Rule (ETR) server is used to manage events, triggers, and rules. Negotiation strategic rules can be added or modified at run-time. A cost-benefit analysis component is used to perform quantitative analysis of alternatives. The use of negotiation servers to conduct automated negotiation has been demonstrated in the context of an integrated supply chain scenario.

Element matching across data-oriented XML sources using a multi-strategy clustering model

We describe a family of heuristics-based clustering strategies to support the merging of XML data from multiple sources. As part of this research, we have developed a comprehensive classification for schematic and semantic conflicts that can occur when reconciling related XML data from multiple sources. Given the fact that element clustering is compute-intensive, especially when comparing large numbers of data elements that exhibit great representational diversity, performance is a critical, yet so far neglected aspect of the merging process. We have developed five heuristics for clustering data in the multi-dimensional metric space. Equivalence of data elements within the individual clusters is determined using several distance functions that calculate the semantic distances among the elements.The research described in this article is conducted within the context of the Integration Wizard (IWIZ) project at the University of Florida. IWIZ enables users to access and retrieve information from multiple XML-based sources through a consistent, integrated view. The results of our qualitative analysis of the clustering heuristics have validated the feasibility of our approach as well as its superior performance when compared to other similarity search techniques.

The IDEAL approach to Internet-based negotiation for e-business

With the emergence of e-business as the next killer application for the Web, automating bargaining-type negotiations between clients (i.e., buyers and sellers) has become increasingly important. With IDEAL (Internet based Dealmaker for e-business), we have developed an architecture and framework, including a negotiation protocol, for automated negotiations among multiple IDEAL servers. The main components of IDEAL are a constraint satisfaction processor (CSP) to evaluate a proposal, an Event-Trigger-Rule (ETR) server for managing and triggering the execution of rules which make up the negotiation strategy (rules can be updated at run-time to deal with the dynamic nature of negotiations), and a cost-benefit analysis to help in the selection of alternative strategies. We have implemented a fully functional prototype system of IDEAL to demonstrate automated negotiations among buyers and suppliers participating in a supply chain.

MUPRET: An Ontology-Driven Traceability Tool for Multiperspective Requirements Artifacts

Multiperspective requirements traceability (MUPRET) tool is resulted from our attempt in resolving the heterogeneity in traceability of multiperspective requirements artifacts. The MUPRET tool facilitates the automatic extraction and construction of requirements elements of an individual stakeholder into a so-called requirements ontology. As a result, multiperspective requirements artifacts of different stakeholders are captured in a common taxonomy imposed by the sharing base of requirements ontology. The tool then automatically generates traceability links by matching requirements ontologies. This paper presents the architecture of the MUPRET tool, together with an illustrative example of its applications.

Inference of lexical ontologies. The LeOnI methodology

In this article we present a method for semi-automatically deriving lexico-conceptual ontologies in other languages, given a lexico-conceptual ontology for one language and bilingual mapping resources. Our method uses a logistic regression model to combine mappings proposed by a set of classifiers (up to 17 in our implementation). The method is formally described and evaluated by means of two implementations for semi-automatically building Spanish and Thai WordNets using Princetons WordNet for English and conventional English-Spanish and English-Thai bilingual dictionaries.

Uncertain inference control in privacy protection

Context management is the key enabler for emerging context-aware applications, and it includes context acquisition, understanding and exchanging. Context exchanging should be made privacy-conscious. We can specify privacy preferences to limit the disclosure of sensitive contexts, but the sensitive contexts could still be derived from those insensitive. To date, there have been very few inference control mechanisms for context management, especially when the environments are uncertain. In this paper, we present an inference control method for private context protection in uncertain environments.

Lexical acquisition and clustering of word senses to conceptual lexicon construction

We describe a mechanism and an algorithm to support construction of a large complex conceptual lexicon from an existing alphabetical lexicon. As part of this research, we define lexical models to present words and lexicons. Given the fact that an alphabetical lexicon contains lexical information about words which are organized by their spelling, constructing a conceptual lexicon requires an identification of lexical concepts and their relationships. Lexical acquisition and word-sense clustering are introduced to identify the lexical concepts and to discover the conceptual relationships. The result of this research is a set of candidate concepts which can be treated as initial concepts for the conceptual lexicon construction.

Deriving Traceability Relationships of Multiperspective Software Artifacts from Ontology Matching

Requirements traceability and change management in multiperspective software artifacts is a major challenge due to the heterogeneity of the artifacts themselves. Our previous attempt in resolving such problem results in a multiperspective requirements traceability framework, namely MUPRET. The key idea of MUPRET is to use ontology, so-called requirements ontology, as a common representation of mutual understanding of semantics of words in the requirements sentences. By doing so, the traceability relationships can be automatically generated when a match is found in the requirements ontologies. Although the MUPRET was originally proposed for the textual requirements, this paper presents the extension of MUPRET to cover different representations of software artifacts, together with an illustrative example of the extended applications.

Khmer POS Tagging Using Conditional Random Fields.

The transformation-based approach with hybrid of rule-based and tri-gram have already been introduced for Khmer part-of-speech (POS) tagging. In this study, in order to further explore this topic, we present an alternative approach to Khmer POS tagging using Conditional Random Fields (CRFs). Since the features greatly affect the tagging accuracy, we investigate five groups of features and use them with the CRF model. First, we study different contextual information and use it as our baseline model. We then analyze the characteristics of Khmer and come up with three additional groups of language-related features including morphemes, word-shapes and name-entities. We also explore the use of lexicon as features to further improve the accuracy of our tagger. Our proposed approach has been evaluated on a corpus of 41,058 words and 27 POS tags. The comparative study has shown that our proposed approach produces a competitive accuracy compared to other Khmer POS tagging approaches.

FING: Thai fingerspelling practice application

This paper describes a design and implementation of FING, Thai Fingerspelling practice mobile application. This application aims to help users learning, practicing, and recognizing Thai fingerspelling, which is the basic of Thai writing for communication of Hearing-Impaired people through playing games. Educative game is one of the methods for learning, which is powerful because game can make learning fun, and make player interest and focus on learning. Confusion of Fingerspelling and frequency of using Thai alphabet are used to be a principle in game design. There are 3 main features in application which are learning, game play, and statistic result. “FING” is appropriate for everyone who interest in learning Thai fingerspelling.