Dae-Young Choi

A new aggregation method in a fuzzy environment

The research and system development work described in this paper is aimed at overcoming some of the problems associated with the development of large, complex linear programming problems. The most overwhelming problem is that of size. It is not uncommon for large planning and policy analysis problems to have tens of thousands of constraints and activities. Matrix generator systems have been designed to help in this process. However, the amount of manual labor involved is still very great and the formulation process is subject to errors which are difficult to detect. We provide an overview of a system which uses artificial intelligence and database techniques to help a knowledgeable user formulate large linear programs. The system automates many of the tedious processes associated with large-scale modeling and provides a top-down development environment with a number of different forms of problem representation.

Personalized local internet in the location-based mobile web search

In this paper, a new ubiquitous-GPS-Web-enabled mobile search mechanism is proposed. It is based on users physical location, distance from users physical location and users search intentions (i.e., keywords, preferences). The concept of perception index (PI) is used to handle fuzzy query in the ubiquitous-GPS-Web-enabled mobile search. Using fuzzy query, together with users physical location and distance from users physical location, the ubiquitous-GPS-Web-enabled mobile devices can receive more personalized and locally targeted search results. The proposed approach can be applied to enhance the power of mobile Web search. Consequently, it gives a mobile user the personalized local angle to make searching for local businesses on the Web, and contributes to a significant convenience in the location-based mobile Web searching (i.e., local Internet).

Enhancing the power of Web search engines by means of fuzzy query

Commercial Web search engines such as Yahoo!, Google, etc., have been defined which manage information only in a crisp way (i.e., keyword-based). Their query languages do not allow the expression of preferences or vagueness. They generally return many Web pages irrelevant to users query. In order to handle these problems, we propose the Perception Index (PI) that contains attributes associated with a focal keyword restricted by fuzzy term(s) used in fuzzy queries on the Internet. The PI assists the user to reflect his/her perception in the process of query. If we integrate the Document Index (DI) used in commercial Web search engines with the proposed PI, we can handle both crisp terms (keyword-based) and fuzzy terms (perception-based). In this respect, the proposed approach is softer than the keyword-based approach. The PI brings somewhat closer to natural language. It is a further step toward a human-friendly, natural language-based interface for Web searching. Consequently, Internet users can narrow thousands of hits to the few that users really want. In this respect, the PI provides a new tool for targeting queries that users really want. In this paper, we also present a personalized search and ranking based on the PI.

ASA and its application to multi-criteria decision making (case study)

Aggregation plays an important role in many applications related to the development of intelligent systems. In a fuzzy environment the existing aggregation operators are generally the t-norm, t-conorm, mean operators, Yagers operator and γ-operator. However, these aggregation operators do not properly reflect the situation in the aggregation process. That is, these types of aggregation operators are independent of the aggregation situation. In order to solve these problems we propose a new aggregation method to reflect the situation in the aggregation process. It is the aggregation based on situation assessment (ASA) method. It consists of the situation assessment model (SAM) and the ASA algorithm. In this ASA method, the SAM is utilized to reflect the situation in the aggregation process. This model generates the parameter, which is controlled by decision-maker. It indicates the current degree of aggregation situation. Therefore, our method can be adapted to certain situations by using the parameter. In this paper, ASA method is applied to the multi-criteria decision making environment.

Aggregation of Preferences Based on FSAM in GDSS

Aggregation plays a central role as a means of combining all opinions that are expressed by group members in a group decision support system (GDSS). In this paper, we propose a new epsiv-ASA (Aggregation based on Situation Assessment) algorithm to reflect a decision situation in the aggregation process. Although some research findings showed the importance of cultural factors in GDSS, most of them did not present how to implement cultural factors in GDSS. To handle this problem, we present a proposal for reflecting status differentials in GDSS. It may be used to reflect cultural differences in GDSS design. It is a further step toward the integration of cultural factors into existing GDSS design.

Toward a voice interface and personalized local web search in smart phones

A new approach for a voice interface and personalized local web search in smart surfing phone is proposed. It is based on voice web search, users physical location, search distance, search directory and users search intentions. In order to handle fuzzy query, perception index (PI) is also proposed. Kinking these issues is technologically demanding and potentially useful in smart phones.

Aggregation of preferences based on FSAM

We propose a new e-ASA (Aggregation based on Situation Assessment) algorithm based on the fuzzy situation assessment model (FSAM) to reflect a situation in the process of aggregation. The proposed aggregation algorithm makes an adaptive aggregation result between min and max depending on the value of parameter representing a degree of situation. It is a further step toward situation-based aggregation.

Integration of document index with perception index

Abstract We propose the perception index (PI) that contains attributes associated with a focal keyword restricted by fuzzy term(s) used in fuzzy queries on the Internet. The PI assists the user to reflect his/her perception in the process of query. If we integrate the document index (DI) used in commercial Web search engines with the proposed PI, we can handle both crisp terms (keyword-based) and fuzzy terms (perception-based). In this respect, the proposed approach is softer than the keyword-based approach. The PI brings somewhat closer to natural language. It is a further step toward a real human-friendly, natural language-based interface for Internet. It should greatly help the user relatively easily retrieve relevant information.

ATM based on SPMF

We propose an approximate transformation method (ATM) based on the standardized parametric membership functions (SPMF). The ATM provides fuzzy systems with the platform for the relatively fast computations by transforming the non-parametric membership functions (NPMF) into the parametric membership functions (PMF). In this paper, we apply the ATM to linguistic approximation.

A New Case-based Approximate Reasoning based on SPMF in Linguistic Approximation.

A new case-based approximate reasoning (CBAR) based on SPMF in linguistic approximation is proposed. It provides an efficient mechanism for linguistic approximation within linear time complexity.