Moohun Lee

Multidimensional Filtering Approach Based on Contextual Information

Existing recommended systems offer calculation of recommendation for user-item with e-commerce. But these systems omit much available information. It is users contextual information. Thus accuracy of recommender systems is relatively lower. Mostly excepted information is difficult to clearly define the attributes and to calculate the values as the numerical data. If this contextual information can be changed into calculable element in recommender system, it can become the improved recommendation technique. This paper proposes multidimensional approach additionally applying contextual information for 2 dimensions based on existing recommendation system

Novel Framework for Policy Based Scheduling and Quality of Service on Grid

We discuss a novel framework for policy based scheduling in resource allocation of grid computing. The framework has several features. First, Efficient resource usage management is achieved by assigning usage quotas to intended users. Second, the scheduling strategy can control the request assignment to grid resources by adjusting resource usage accounts or request priorities. Third, quality of service feature allows special privileges to various classes of requests, users, groups, etc. Experimental results are provided to demonstrate the usefulness of the framework.

Policy Based Scheduling for Resource Allocation on Grid

In this paper we discuss a novel framework for policy based scheduling in resource allocation of grid computing. The framework has several features that are associated with the scheduling strategy, efficient resource management, the scheduling method and Quality of Service(QOS). Experimental results are provided to demonstrate the usefulness of the framework.

Auditing System Using Rule-Based Reasoning in Ubiquitous Computing

We can use information and software of various forms without being restricted for place and time if ubiquitous computing age comes. However, its dysfunction is causing security problems such as outflow of personal information, hacking, diffusion of virus. Specially, dissemination of software that has malicious purpose in ubiquitous computing environment causes serious damage. We have studied about malicious code detection and software vulnerability detection tool to prevent this. But, existent detection tools are not suited to general software, because they are limitative in specification area. In addition, they can not detect a newly appeared malicious code. We must update pattern of new malicious code, because they use a simple pattern matching technique. In this paper, we propose rule-based auditing system that analyzes structure of target code to solve these problems, define this as rule, and detect malicious codes and software vulnerabilities. Proposed auditing system can construct secure ubiquitous computing environment, because it will be used by a common software audit system that reason about source codes security.

Context Model of User Aspect in Context-Awareness

It is very important to model the acquired context to store and manage for context-awareness. Diverse modeling method has been studied and used. But there are several problems. Most models are represented by relational property and modeled with object-centered. It also needs other model to use in other field. Aspect of context-awareness can be changed according as the nucleus is an object or user. In this paper, we interpret with user aspect and propose the context model to resolve the problems. We defined appropriate context that fit to user-centered context model through diverse definition of context.

Schemas Matching Approach Using the Functional Relations

Most of schema matching focuses on computing direct matches between two schemas. However the direct matching is rare. To make more effective schema matching, the indirect matching must utilize in matching processes. The indirect matching can be computed through the relations between schemas. For the indirect matching, ontology based approaches have studied. However, they do not consider the functional relation because the functional relations are difficult to obtain from schemas or ontologies. In this paper, we define the functional relations. And we present the schema matching approach using the functional relations.

A Scheduling Middleware for Scheduling on a Grid Environment

A grid consists of high-end computational, storage, and network resources that, while known a priori, are dynamic with respect to activity and availability. Efficient scheduling of requests to use grid resources must adapt to this dynamic environment while meeting administrative policies. This paper discusses the necessary requirements of such a scheduler and proposes a framework that can administrate grid policies and schedule complex. The paper design allows for a number of functional modules to flexibly plan and schedule workflows representing multiple applications on the grids. It also allows for performance evaluation of multiple algorithms for each functional module. We present early experimental results that effectively utilizes other grid infrastructure such as workflow management systems and execution systems

Weight Based Technique For Improvement Of New User Recommendation Performance

Today, many services and products that used to be only provided on offline have been being provided on the web according to the improvement of computing environment and the activation of web usage. These web-based services and products tend to be provided to customer by customer`s preferences. This paradigm that considers customer`s opinions and features in selecting is called personalization. The related research field is a recommendation. And this recommendation is performed by recommender system. Generally the recommendation is made from the preferences and tastes of customers. And recommender system provides this recommendation to user. However, the recommendation techniques have a couple of problems; they do not provide suitable recommendation to new users and also are limited to computing space that they generate recommendations which is dependent on ratings of products by users. Those problems has gathered some continuous interest from the recommendation field. In the case of new users, so similar users can`t be classified because in the case of new users there is no rating created by new users. The problem of the limitation of the recommendation space is not easy to access because it is related to moneywise that the cost will be increasing rapidly when there is an addition to the dimension of recommendation. Therefore, I propose the solution of the recommendation problem of new user and the usage of item quality as weight to improve the accuracy of recommendation in this paper.

A Novel Weight for Recommendation: Item Quality

The many researches of recommendation technique already have been performed. These techniques were used mostly content-based filtering, collaborative filtering or hybrid filtering approach. They are performed the recommendation using userpsilas rating, user similarity, itempsilas features, user profiles. They consider several features of user and user profiles but they do not consider a quality of items itself. Because they donpsilat be able to efficiently define the quality definition of all item and they donpsilat be able to easily get user feedbacks. To solve the difficulty of the measurement of item quality and apply item quality as a weight to recommendation techniques, we measure item quality through popularity of item and user awareness. And we propose an approach to apply item quality to recommendation.

A recommendation using item quality

Today there are a lot of recommender systems operating on the web. These systems use content-based filtering or collaborative filtering or hybrid approach that was studied before. These techniques operate recommendation by using features of user and item, similarity of users, and items. Even though there is a consideration of attributes of items and users, but there is not much consideration of the quality of items. This is why item quality is not easy to be measured. This paper computes item quality, suggests it to apply to the recommender system, and presents it by analyzing the influence.