A Novel Approach for Microblog Message Ranking Based on Trust Model and Content Similarity

Bei Li,Yanjie Liu 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.3

With the development of social network such as microblog, the number of microblog users increases rapidly. The problem of information overload caused by a large amount of data generated by users is becoming more and more serious. In order to mine the messages which specific users are interested in, we measure social relationship and interactive relationship of users respectively in this paper and propose the trust model based on the user’s direct trust and indirect trust. By means of the trust model, we select the specific user’s candidate user set from a large number of users. We measure the content similarity of messages in the candidate user set and propose a message ranking approach based on user trust model and content similarity. We analyze and compare the ranking results with users’ real behavior in microblog platform. The experiment results show that the approach can accurately rank the microblog messages which the specific users are interested in.

Development of Tag Ranking-Based Image Search System

Si-Hwa Lee,Dae-Hoon Hwang,Sae-Hong Cho 보안공학연구지원센터 2014 International Journal of Software Engineering and Vol.8 No.2

효율적인 소셜 검색을 위한 토픽기반 소셜 관계 랭크 알고리즘

김영안(Young-an Kim),박건우(Gun-woo Park) 한국통신학회 2013 韓國通信學會論文誌 Vol.38 No.5B

지난 10여 년간, 정보기술 분야의 패러다임은 기계중심에서 인간중심으로, 기술기반에서 사용자가 쉽게 정보시스템에 참여하고 활용 할 수 있는 사용자 기반으로 변화되었다. 즉 소셜 네트워크를 이용하여 정보를 상호 공유하는 소셜 검색의 형태로 변화하고 있으며, 이와 같이 사람과 사람을 연결 해 주는 소셜 네트워크 서비스는 웹서비스와 융합을 통해 친구 맺기, 친구 찾기, 유사한 관심사를 갖고 있는 사람들과의 정보공유, 선호도 검색, 정보추천시스템 등 다양한 분야에 활용되고 있다. 본 논문에서는 토픽 기반 소셜 관계 랭크(TS_SRR : Topic Sensitive_Social Relation Rank) 알고리즘을 제안한다. 제안 알고리즘은 소셜 네트워크 서비스를 웹 검색 엔진과 통합하는 것을 목적으로 하며, 소셜 관계 지수, 즉 Social Relation Rank와 검색 결과에 대한 선호도 사이의 상관관계를 분석하였다. 실험 과정에서 소셜 네트워크 안에 존재하는 일반적인 사람들은 정보 공유시 특정 분야에 대해 관심사가 유사할 경우 잘 모르는 타인들에 비해 친밀도가 높은 친구를 더 신뢰한다는 것을 확인 할 수 있었다. 따라서 제안 알고리즘은 소셜 검색의 신뢰성을 향상 시킬 수 있을 것으로 판단된다. In the past decade, a paradigm shift from machine-centered to human-centered and from technology-driven to user-driven has been witnessed. Consequently, Social search is getting more social and Social Network Service (SNS) is a popular Web service to connect and/or find friends, and the tendency of users interests often affects his/her who have similar interests. If we can track users’ preferences in certain boundaries in terms of Web search and/or knowledge sharing, we can find more relevant information for users. In this paper, we propose a novel Topic Sensitive_Social Relationship Rank (TS_SRR) algorithm. We propose enhanced Web searching idea by finding similar and credible users in a Social Network incorporating social information in Web search. The Social Relation Rank between users are Social Relation Value, that is, for a different topics, a different subset of the above attributes is used to measure the Social Relation Rank. We observe that a user has a certain common interest with his/her credible friends in a Social Network, then focus on the problem of identifying users who have similar interests and high credibility, and sharing their search experiences. Thus, the proposed algorithm can make social search improve one step forward.

Re-Ranking Retrieval Model Based on Two-Level Similarity Relation Matrices

Hee-Ju Eun 보안공학연구지원센터 2015 International Journal of Software Engineering and Vol.9 No.12

Web-based specialized retrieval systems for scientific fields extremely restrict the expression for user's information requests. Therefore the process of information content analysis and that of the information acquisition become inconsistent. In this paper, we apply the fuzzy retrieval model to solve the high time complexity of the retrieval system by constructing a reduced term set for the term's relatively important degree. We also perform a cluster retrieval to reflect the user's query exactly through the similarity relation matrix satisfying the characteristics of the fuzzy compatibility relation. This paper proves the performance of a proposed re-ranking model based on the union of similarity of the fuzzy retrieval model and the document cluster retrieval model.

이미지 데이터베이스 유사도 순위 매김 알고리즘

차광호(Guang-Ho Cha) 한국정보과학회 2009 정보과학회논문지 : 데이타베이스 Vol.36 No.5

이 논문은 이미지 데이터베이스를 위한 유사도 순위 매김 알고리즘을 제시한다. 이미지 검색의 문제점 중 하나가 이미지로부터 자동적으로 계산한 하위 레벨 특성과 인간 지각과의 의미 차이이며, 검색시에 이미지 유사도 측정을 위해 많은 알고리즘에서는 민코프스키 측정법(L<SUB>p</SUB>-norm)을 사용하고 있다. 그러나 민코프스키 측정법은 인간 시각 시스템의 비선형적 특성과 문맥 정보를 반영하지 못한다. 본 알고리즘에서는 인간 지각의 비선형성과 문맥 정보를 반영하는 유사도와 탐색 알고리즘을 통해 이 문제를 해결한다. 본 알고리즘을 필기체 숫자 이미지 데이터베이스에 적용하여 성능의 우수성과 효과를 증명하였다. In this paper, we propose a similarity search algorithm for image databases. One of the central problems regarding content-based image retrieval (CBIR) is the semantic gap between the low-level features computed automatically from images and the human interpretation of image content. Many search algorithms used in CBIR have used the Minkowski metric (or Lp-norm) to measure similarity between image pairs. However those functions cannot adequately capture the aspects of the characteristics of the human visual system as well as the nonlinear relationships in contextual information. Our new search algorithm tackles this problem by employing new similarity measures and ranking strategies that reflect the nonlinearity of human perception and contextual information. Our search algorithm yields superior experimental results on a real handwritten digit image database and demonstrates its effectiveness.

Services Rank by Semantic Similarity

Hui Peng 보안공학연구지원센터 2014 International Journal of u- and e- Service, Scienc Vol.7 No.5

Services can be described by their semantics to improve the precision of services discovery. OWL-S describes services semantic by their inputs, outputs, precondition and effects. In the frame of OWL-S, domain ontology concepts are used to describe the semantic of inputs, outputs, precondition and effects of a service in this paper. A service rank algorithm based on the semantic similarity of ontology concepts is introduced, and a travel service discovery example shows the algorithm is effective.

이상탐지 기반의 효율적인 시계열 유사도 측정 및 순위화

최지현 ( Ji-hyun Choi ),안현 ( Hyun Ahn ) 한국인터넷정보학회 2024 인터넷정보학회논문지 Vol.25 No.2

시계열 분석은 시간 순서로 정렬된 데이터로부터 다양한 정보와 인사이트를 발견하기 위한 방법으로 많은 조직에서 비즈니스 문제 해결을 위해 적용하고 있다. 그중에서 시계열 유사도 측정은 패턴이 비슷한 시계열들을 식별하기 위한 단계로서 시계열 검색 및 군집화와 같은 시계열 분석 응용에서 매우 중요하다. 본 연구에서는 전체 시계열이 아닌 이상치들을 중심으로 시계열 유사도 측정을 계산효율적으로 수행하는 방법을 제안한다. 이와 관련하여 이상탐지를 통해 추출된 서브시퀀스 집합에 대한 유사도 측정 결과와 시계열 전체에 대한 유사도 측정 결과 사이의 순위 상관관계를 측정 및 분석하여 제안 방법을 검증한다. 실험 결과로써, 주식 종목 시계열 데이터에 이상치 비율 10%을 적용한 유사도 측정으로부터 최대 0.9 이상의 스피어만 순위 상관계수를 확인하였다. 결론적으로 제안 방법을 통해 시계열 유사도 측정에 소요되는 계산량을 유의미하게 절감하는 동시에 신뢰 가능한 시계열 검색 및 군집화 결과를 기대할 수 있다. Time series analysis is widely employed by many organizations to solve business problems, as it extracts various information and insights from chronologically ordered data. Among its applications, measuring time series similarity is a step to identify time series with similar patterns, which is very important in time series analysis applications such as time series search and clustering. In this study, we propose an efficient method for measuring time series similarity that focuses on anomalies rather than the entire series. In this regard, we validate the proposed method by measuring and analyzing the rank correlation between the similarity measure for the set of subsets extracted by anomaly detection and the similarity measure for the whole time series. Experimental results, especially with stock time series data and an anomaly proportion of 10%, demonstrate a Spearman’s rank correlation coefficient of up to 0.9. In conclusion, the proposed method can significantly reduce computation cost of measuring time series similarity, while providing reliable time series search and clustering results.

Site Specific Soil Fertility Ranking and Seasonal Paddy Variety Selection : An Intuitionistic Fuzzy Rough Set and Fuzzy Bayesian Based Decision Model

K. Lavanya,M. A. Saleem Durai,N. Ch. S. N. Iyengar 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.6

In decision making, crisp ranking is not possible when the entire attribute characteristics and their degree of importance are known precisely. In real world situations decision making takes place in an environment where the goals, the constraints, and the consequences of possible actions are not known precisely. Thus the best condition for classic decision making problem may not be satisfied when the situation involves both fuzzy and crisp data. Site specific soil fertility and seasonal crop selection data are characterized by high degree of fuzziness and uncertainty. In our model, intuitionistic fuzzy rough set establishes a close connection between the concepts of similarity and dissimilarity thereby providing an excellent framework for ranking soil fertility. Further fuzzy Bayesian incorporates both fuzzy and uncertainty in the probability model yielding more realistic seasonal paddy variety selection. The decision model introduced in this paper is suitable for both data rich and data poor environment. The results illustrate that the soil fertility ranking and successive paddy variety selection can help to sustain the soil fertility in subsequent rotations and minimize the loss of nutrients from the sites.

음운 과정과 유사성: 영어의 동화 현상 분석

조형묵 한국중원언어학회 2019 언어학연구 Vol.0 No.53

The present study provides a correspondence-theoretic account of assimilation processes in English and their relation to hierarchies of constraints. This work is couched within Surface Correspondence Theory and correspondence relations in this approach parallels those between input and output, except that this approach defines correspondence among segments in the surface. In this theory, phonological processes are analyzed by constraints that require and limit correspondence among similar segments. Analyzing different modes of English Nasal Assimilation and Stop Assimilation (e.g., total assimilation, partial assimilation, no assimilation), this paper shows that the different modes of assimilation are connected with the hierarchy of constraints defining correspondence among segments. For instance, the constraints that require correspondence between most similar segments or identical segments are on the higher position in the ranking of constraints. This is in accordance with the original assumption of Surface Correspondence Theory. On the basis of this theoretical assumption, this paper analyzes total assimilation and partial assimilation in English, and the results show selection of optimal outputs.

A Study on Fuzzy Ranking Model based on User Preference

Kim Dae-Won Korean Institute of Intelligent Systems 2006 한국지능시스템학회논문지 Vol.16 No.3

A great deal of research has been made to model the vagueness and uncertainty in information retrieval. One such research is fuzzy ranking models, which have been showing their superior performance in handling the uncertainty involved in the retrieval process. In this study we develop a new fuzzy ranking model based on the user preference. Through the experiments on the TREC-2 collection of Wall Street Journal documents, we show that the proposed method outperforms the conventional fuzzy ranking models.