Subject-Balanced Intelligent Text Summarization Scheme (주제 균형 지능형 텍스트 요약 기법)
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- Journal of Intelligence and Information Systems
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- v.25 no.2
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- pp.141-166
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- 2019
Recently, channels like social media and SNS create enormous amount of data. In all kinds of data, portions of unstructured data which represented as text data has increased geometrically. But there are some difficulties to check all text data, so it is important to access those data rapidly and grasp key points of text. Due to needs of efficient understanding, many studies about text summarization for handling and using tremendous amounts of text data have been proposed. Especially, a lot of summarization methods using machine learning and artificial intelligence algorithms have been proposed lately to generate summary objectively and effectively which called "automatic summarization". However almost text summarization methods proposed up to date construct summary focused on frequency of contents in original documents. Those summaries have a limitation for contain small-weight subjects that mentioned less in original text. If summaries include contents with only major subject, bias occurs and it causes loss of information so that it is hard to ascertain every subject documents have. To avoid those bias, it is possible to summarize in point of balance between topics document have so all subject in document can be ascertained, but still unbalance of distribution between those subjects remains. To retain balance of subjects in summary, it is necessary to consider proportion of every subject documents originally have and also allocate the portion of subjects equally so that even sentences of minor subjects can be included in summary sufficiently. In this study, we propose "subject-balanced" text summarization method that procure balance between all subjects and minimize omission of low-frequency subjects. For subject-balanced summary, we use two concept of summary evaluation metrics "completeness" and "succinctness". Completeness is the feature that summary should include contents of original documents fully and succinctness means summary has minimum duplication with contents in itself. Proposed method has 3-phases for summarization. First phase is constructing subject term dictionaries. Topic modeling is used for calculating topic-term weight which indicates degrees that each terms are related to each topic. From derived weight, it is possible to figure out highly related terms for every topic and subjects of documents can be found from various topic composed similar meaning terms. And then, few terms are selected which represent subject well. In this method, it is called "seed terms". However, those terms are too small to explain each subject enough, so sufficient similar terms with seed terms are needed for well-constructed subject dictionary. Word2Vec is used for word expansion, finds similar terms with seed terms. Word vectors are created after Word2Vec modeling, and from those vectors, similarity between all terms can be derived by using cosine-similarity. Higher cosine similarity between two terms calculated, higher relationship between two terms defined. So terms that have high similarity values with seed terms for each subjects are selected and filtering those expanded terms subject dictionary is finally constructed. Next phase is allocating subjects to every sentences which original documents have. To grasp contents of all sentences first, frequency analysis is conducted with specific terms that subject dictionaries compose. TF-IDF weight of each subjects are calculated after frequency analysis, and it is possible to figure out how much sentences are explaining about each subjects. However, TF-IDF weight has limitation that the weight can be increased infinitely, so by normalizing TF-IDF weights for every subject sentences have, all values are changed to 0 to 1 values. Then allocating subject for every sentences with maximum TF-IDF weight between all subjects, sentence group are constructed for each subjects finally. Last phase is summary generation parts. Sen2Vec is used to figure out similarity between subject-sentences, and similarity matrix can be formed. By repetitive sentences selecting, it is possible to generate summary that include contents of original documents fully and minimize duplication in summary itself. For evaluation of proposed method, 50,000 reviews of TripAdvisor are used for constructing subject dictionaries and 23,087 reviews are used for generating summary. Also comparison between proposed method summary and frequency-based summary is performed and as a result, it is verified that summary from proposed method can retain balance of all subject more which documents originally have.
The present study was conducted to analyze the degree of changes in knowledge and attitude toward health, arid health promoting activities after providing health education intervention for a year to elementary school children, to examine the factors effecting knowledge, attitude and health promoting practices for obesity and diet, and to analyze whether changes are present in health level according to changes in knowledge on health and health promoting activities. After conducting a pre-survey rio 354 subjects of 3rd and 4th grade students and their mothers in the city area of Kyungju, in April, 1999, 301. responses with the responding rate of 85% were obtained. Final analysis was done with 231 pairs of a student and his/her mother who could be followed up after a year among 301 pairs of the respondents, excluding those students who transferred, those who were excused from school early, those who did not take abdominal fat measurements, and those students and mothers respondents whose survey was incomplete. Based on the changes before and after the intervention, the scores on knowledge about obesity and diet showed a significant difference in normal weight group, and the scores on the attitude toward obesity and diet increased significantly in obesity group but decreased significantly in normal weight group(p<0.01). The scores of practicing health promoting activities were significantly increased in both groups, and although the waist-hip ratio (WHR) did not change in obesity group, the rate increased significantly in normal weight group(p<0.01). As for changes on the knowledge of obesity and diet before and after the intervention while dividing the scores into 3 levels based on the scores of the pre-survey and compared to changes in the scores one year after, in the case of the changes in the scores in the 1st third, the score on the knowledge about obesity and diet changed from 1.3 in the pre survey to 3.7 after the intervention, showing significant increase(p<0.01) The scores of practicing health promoting activities for obesity and diet were significantly increase in all three levels(p<0.01), and the degree of changes in the scores was 7.0 points in the 1st third, 4.4 points for the and third and 1.8 points for the 3rd third, showing a significant difference among the three levels(p<0.01). It was shown that the increase in BMI in those students whose mothers have the education level higher than university was significantly higher than the increase in BMI in those students whose mothers have the education level under high school, and those students whose mothers are in their 30's showed higher changes in practicing health promoting activities for obesity and diet. When the scores of mothers' knowledge and attitude toward obesity and diet were compared by dividing the scores into tertile, the score of students' knowledge changed significantly according to the scores of mothers' attitude toward obesity and diet. In multiple regression analysis on changes in the scores of knowledge about obesity and diet, the student variables of the degree of awareness on the seriousness of obesity, and the scores of previous knowledge on diet and obesity were selected the significant variables, and among the mother variables, the degree of guiding the child on diet and the education level were the significant variables. In multiple regression analysis to analyze the factors effecting changes in the attitude toward obesity and diet, the student variables of the BMI, scores of previous knowledge on obesity and diet, and scores on the previous attitude toward obesity and diet were shown to be significant. In multiple regression analysis on the factors effecting changes in health promoting activities for obesity and diet, the student variables of the BMI, scores on the previous attitude toward obesity and diet, and changes in the scores of obesity and diet were selected the significant variables.