Journal of Intelligence and Information Systems,
Vol. 13, No. 1, March 2007
An Automatic Generation Method of the Initial Query Set for Image Search on the Mobile Internet
Deok-Hwan Kim, and Yoon-Ho Cho
Vol. 13, No. 1, Page: 1 ~ 14
Keywords : Mobile Internet, Collaborative Filtering, Content Based Image Retrieval, Relevance Feedback
Character images for the background screen of cell phones are one of the fast growing sectors of the mobile content market. However, character image buyers currently experience tremendous difficulties in searching for desired images due to the awkward image search process. Content-based image retrieval (CBIR) widely used for image retrieval could be a good candidate as a solution to this problem, but it needs to overcome the limitation of the mobile Internet environment where an initial query set (IQS) cannot be easily provided as in the PC-based environment. We propose a new approach, IQS-AutoGen, which automatically generates an initial query set for CBIR on the mobile Internet. The approach applies the collaborative filtering (CF), a well-known recommendation technique, to the CBIR process by using users' preference information collected during the relevance feedback process of CBIR. The results of the experiment using a PC-based prototype system show that the proposed approach successfully satisfies the initial query requirement of CBIR in the mobile Internet environment, thereby outperforming the current image search process on the mobile Internet
Detection and Analysis of the Liver Area and Liver Tumors in CT Scans
Kwang-Baek Kim
Vol. 13, No. 1, Page: 15 ~ 27
Keywords : Contrast-enhancement CT, Liver Tumor, Hypervascular Tumor
In Korea, hepatoma is the thirdly frequent cause of death from cancer occupying 17.2% among the whole deaths from cancer and the rate of death from hepatoma comes to about 21's persons per one-hundred thousand ones. This paper proposes an automatic method for the extraction of areas being suspicious as hepatoma from a CT scan and evaluates the availability as an auxiliary tool for the diagnosis of hepatoma. For detecting tumors in the internal of the liver from CT scans, first, an area of the liver is extracted from about??CT scans obtained by scanning in 2.5-mm intervals starting from the lower part of the chest. In the extraction of an area of the liver, after unconcerned areas outside of the ribs being removed, areas of the internal organs are separated and enlarged by using intensity information of the CT scan. The area of the liver is extracted among separated areas by using information on position and morphology of the liver. Since hepatoma is a hypervascular turner, the area corresponding to hepatoma appears more brightly than the surroundings in contrast-enhancement CT scans, and when hepatoma shows expansile growth, the area has a spherical shape. So, for the extraction of areas of hepatoma, areas being brighter than the surroundings and globe-shaped are selected as candidate ones in an area of the liver, and then, areas appearing at the same position in successive CT scans among the candidates are discriminated as hepatoma. For the performance evaluation of the proposed method, experiment results obtained by applying the proposed method to CT scans were compared with the diagnoses by radiologists. The evaluation results showed that all areas of the liver and liver tumors were extracted exactly and the proposed method has a high availability as an auxiliary diagnosis tools for the discrimination of liver tumors.
A Context Model Comparison Methodology for Developing Generic Context Model used in Ubiquitous Multi-Services
Tea Huan Park , and Kwon Ohbyung
Vol. 13, No. 1, Page: 29 ~ 47
Keywords : Ubiquitous Environment, Context Model, Context Aware System
Acquiring context data in a timely and correct way is now regarded as one of the crucial characteristics of the proactive service which runs on ubiquitous computing environment. Moreover, context model should be well designed to provide a solid context-aware system. Since the ubiquitous computing systems aim to provide context-aware services everywhere with any available devices, legacy services which uses context models assuming single or limited domain should be extended enough to be useful even for multi-domain muli-services. This leads us to a motivation to build a generic context model with an appropriate type of model. Hence, the purpose of this paper is to propose a generic context model by assessing a variety of model types with a sort of evaluation measures.
Vehicle Routing Based on Pickup and Delivery in a Ubiquitous Environment : u-MDPDPTW
Yong Sik Chang, and Hyun Jung Lee
Vol. 13, No. 1, Page: 49 ~ 58
Keywords : Supply Chain, Vehicle Routing, Integer Programming, u-MDPDPTW
MDPDPTW (Multi-Depot Pickup and Delivery Problem with Time Windows) is a typical model among the optimization models based on the pickup and delivery flow in supply chains. It is based on multi-vehicles in multi-depots and does not consider moving vehicles near pickup and delivery locations. In ubiquitous environments, it is possible to obtain information on moving vehicles and their baggage. Providing the proper context from the perspective of moving vehicles and their baggage allows for more effective vehicle routings. This study proposes Integer Programming-based MDPDPTW including the information on moving vehicles and their baggage in a ubiquitous environment: u-MDPDPTW, and shows the viability and effectiveness of u-MDPDPTW through comparative experiments of MDPDPTW and u-MDPDPTW.
Social Network-Based Knowledge Management System for P2P Environment
Youn-Sang Kim, and Suhn Beom Kwon
Vol. 13, No. 1, Page: 59 ~ 79
Keywords : P2P, KMS, Social Network
P2P (Peer to Peer) techniques have been well applied to file sharing due to its cost-effectiveness and convenience. Dynamic network evolution is another good thing for P2P according to addition and deletion of nodes and change of files a node has. Our research proposes a P2P-based KMS (Knowledge Management System). Knowledge of enterprises spreads all over sub-organizations like oversea factories and sales departments and is changed in dynamic manner. P2P techniques are, therefore well matched with knowledge management domain. In order to increase search efficiency, we introduce social network theory into P2P-based KMS. Social network technique makes the most similar nodes (in KMS domain, nodes which has the most similar knowledge) its own neighbors, which makes eventually search efficiency increase. We developed our prototype system P2P-SN-KMS and evaluated by simulation.
An Intelligent Self Health Diagnosis System using FCM Algorithm and Fuzzy Membership Degree
Kwang-Baek Kim, and Ju-Sung Kim
Vol. 13, No. 1, Page: 81 ~ 90
Keywords : Intelligent Disease Diagnosis System, Modified FCM Algorithm, Pattern Distribution
This paper shows an intelligent disease diagnosis system for public. Our system deals with 30 diseases and their typical symptoms selected based on the report from Ministry of Health and Welfare, Korea. Technically, the system uses a modified FCM algorithm for clustering diseases and the input vector consists of the result of user-selected questionnaires. The modified FCM algorithm improves the quality of clusters by applying symmetrically measure based on the fuzzy theory so that the clusters are relatively sensitive to the shape of the pattern distribution. Furthermore, we extract the highest 5 diseases only related to the user-selected questionnaires based on the fuzzy membership function between questionnaires and diseases in order to avoid diagnosing unrelated disease.
Web-based Product Recommendation System with Probability Similarity Measure
Sang Hyun Choi, and Byeong Seok Ahn
Vol. 13, No. 1, Page: 91 ~ 105
Keywords : Personalized Recommendation, Similarity Measure, Collaborative Commerce
This research suggests a recommendation system that enables bidirectional communications between the user and system using a utility range-based product recommendation algorithm in order to provide more dynamic and personalized recommendations. The main idea of the proposed algorithm is to find the utility ranges of products based on user specified preference information and calculate the similarity by using overlapping probability of two range values. Based on the probability, we determine what products are similar to each other among the products in the product list of collaborative companies. We have also developed a Web-based application system to recommend similar products to the customer. Using the system, we carry out the experiments for the performance evaluation of the procedure. The experimental study shows that the utility range-based approach is a viable solution to the similar product recommendation problems from the viewpoint of both accuracy and satisfaction rate.

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