• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.4
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• pp.301-306
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• 2008

Purpose: Recently, a number of patients needed total thyroidectomy and high dose radioiodine therapy (HD-RAI) get increased more. The aim of this study is to evaluate whether pathological staging (PS) and serum thyroglobulin (sTG) level could replace the diagnostic I-123 scan for the determination of therapeutic dose of HD-RAI in patients with differentiated thyroid cancer. Materials and Methods: Fifty eight patients (M:F=13;45, age $44.5{\pm}11.5\;yrs$) who underwent total thyroidectomy and central or regional lymph node dissection due to differentiated thyroid cancer were enrolled. Diagnostic scan of I-123 and sTG assay were also performed on off state of thyroid hormone. The therapeutic doses of I-131 (TD) were determined by the extent of uptakes on diagnostic I-123 scan as a gold standard. PS was graded by the criteria recommended in 6th edition of AJCC cancer staging manual except consideration of age. For comparison of the determination of therapeutic doses, PS and sTG were compared with the results of I-123 scan. Results: All patients were underwent HD-RAI. Among them, five patients (8.6%) were treated with 100 mCi of I-131, fourty three (74.1%) with 150 mCi, six (10.3%) with 180 mCi, three (5.2%) with 200 mCi, and one (1.7%) with 250 mCi, respectively. On the assessment of PS, average TDs were $154{\pm}25\;mCi$ in stage I (n=9), $175{\pm}50\;mCi$ in stage II (n=4), $149{\pm}21\;mCi$ in stage III (n=38), and $161{\pm}20\;mCi$ in stage IV (n=7). The statistical significance was not shown between PS and TD (p=0.169). Among fifty two patients who had available sTG, 25 patients (48.1%) having below 2 ng/mL of sTG were treated with $149{\pm}26\;mCi$ of I-131, 9 patients (17.3%) having $2{\leq}\;sTG\;<5\;ng/mL$ with $156{\pm}17\;mCi$, 5 patients (9.6%) having $5{\leq}\;sTG\;<10\;ng/mL$ with $156{\pm}13\;mCi$, 7 patients (13.5%) having $10{\leq}sTG\;<50\;ng/mL$ with $147{\pm}24\;mCi$, and 6 patients (11.5%) having above 50 ng/mL with $175{\pm}42\;mCi$. The statistical significance between sTG level and TD (p=0.252) was not shown. Conclusion: In conclusion, PS and sTG could not replace the determination of TD using I-123 scan for first HD-RAI in patients with differentiated thyroid cancer.

• Tuberculosis and Respiratory Diseases
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• v.46 no.5
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• pp.674-684
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• 1999

Background : It has been generally known that the incidence of lung cancer is higher in the patients with idopathic pumonary fibrosis (IPF) than those in general population. The reported incidence was variable from 4.8 to 43.2%. There were controversies on the most frequent cell type (squamous cell carcinoma vs. adenocarcinoma) and no study was done about the real concordance of cancer and the fibrotic lesion. And the pulmonary fibrosis may influence not only the development of cancer but also the treatment and prognosis of the cancer, but there was no report on that point. Method : Total 63 patients ($66.8{\pm}7.8$ year, M : F=61 : 2) were diagnosed as IPF combined with lung cancer (IFF-CA) at Asan Medical Center. A retrospective analysis was done about the risk factors of the lung cancer, pulmonary function test, the site of cancer(especially the relationship of the cancer with the fibrotic lesion), the histologic types, and the stage of cancer. The histologic types were compared with those of 2,660 patients with lung cancer who were diagnosed at the same institute for the same period. The effect of IPF on the treatment of the cancer was evaluated with the survival time after the detection of lung cancer. Results : The lung cancer was found in 63(22.9%) out of 281 patients with IPF. But in most of them(45 patients), lung cancer was detected at the same time with IPF and only in 18 patients, the cancer was diagnosed during the follow-up($25.2{\pm}17.7$ months) of IPF. So in our study, 6.7% of patients with IPF developed lung cancer during the course of the disease. The age ($66.8{\pm}7.84$ vs. $63.4{\pm}11.1$ years), percentage of smoker (88.9 vs. 67.2%), and the male gender (96.8 vs. 67.6%) were significantly higher in IPF-CA compared with lone IPF (p<0.05). The odds ratio of smoking was 4.7 compared with non smoking IPF controls. The lung cancer was located more frequently in the upper lobe and 55.5% was in the periphery of lung. The cancer was developed in the fibrotic lesion in 23 patients (35.9%), and in the majority of the patients, the cancer was separated from the fibrosis. The cell type of the lung cancer in IPF-CA was squamous cell carcinoma 34.9%, adenocarcinoma 30.2%, small cell carcinoma 19.0%, large cell undifferenciated carcinoma 6.3%, and others 9.5%. No significant difference in the distribution of histologic type of the lung cancer was found between IPF-CA and lone lung cancer. There was no significant difference in demographic features, cell types, location and the stage of the cancer between the group with concurrent IPF-CA and the group with cancer diagnosed during the follow up of IPF. There was a tendency (but statistically not significant : p=0.081) of higher incidence of adenocarcinoma among the cancers developed in the fibrotic area(43.5%) (F-CA) than in the cancers in non-fibrotic area (22.5%) (NF-CA). The prognosis of the patients with F-CA was poor (median survival : 4 months) compared with the patients with NF-CA (7 months, p=0.013), partly because the prevalence of severe IPF (the extent of fibrosis in HRCT 50%) was higher in F-CA group. Conclusion : These data suggest that the lung cancer in the patients with IPF has similar features to the ordinary lung cancer.