Incorporating Social Relationship discovered from User's Behavior into Collaborative Filtering (사용자 행동 기반의 사회적 관계를 결합한 사용자 협업적 여과 방법)
-
- Journal of Intelligence and Information Systems
- /
- v.19 no.2
- /
- pp.1-20
- /
- 2013
Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.
Conserving the recored cultural inheritance is actually the duty of all of us. Above all, the management and conservation of archives and documents is up to archivists who have technical knowledge about archival science. Archivists have to not only conserve archives and documents but also carry out classifying and appraising them in order to define them as current historic ones. The fundamental education about archival science is made up of history and law. Because Archive is the organisation which manage archives and documents produced by legal and administrative actions. Although there are still arguments about technical knowledge and degree archivists have to acquire, most of them prefer the studies related with history and emphasize legal studies to be the general boundary of archivits' ideology and trust. The training course about conservation of archives is conducted in about 9 National Archives of Torino, Milano, Venezia, Genova, Bologna, Parma, Roma, Napoli, Palermo. The training course in 19th was mostly based on the lectures of Phaleography, Diplomatics. There were not the education about archival science yet. Toward the end of 19th and 20th, people stressed the most basic subject in the training course of National Archive was not Phaleography and Diplomatics but archival science. The goal of archival science is to study the institution and organisation transferring archives and documents to Archive. And also it help archivists not wander about with ignorance of organisational and original procedures and divisions but know exactly theirs works. Like this, the studies on institution and organisation have got in the saddle as a branch of archival science since a few ten years. While archival science didn't evoke sympathy among people and experienced the tedious and difficult path in italy and other countries, Archive was managed by experts of other branches. As a result, there were a lot of faults in Archival Science. Specializing training course for Italian archivists came into being under the backdrop of Social Science Institute of Roma National University in 1925. The archival course of universities accomplished by the studies of history, law and economy. And such as Eugenio Casanova and Giorgio Cencetti were devoted archival science was abled to settle down in national archive. The training course for experts of 'archival science, 'Phaleography and Diplomatics' in National Archive of Bologna(Archivio di Stato di Bologna) is one of courses conducted in 17 National Archives in italy. This course is gratuitous and made up of 8 subjects(Archivistica, Paleografia, Diplomatica, Storia dell' Archivio, Notariato e documenti privati, istituzione medievale, istituzione moderna, istituzione contemporanea) students have to complete for two years. Students can receive the degree through passing twice written exam and once oral test. After department of Culture and education finally puts the marks of students, the chief Nationa Archive of Bologna confer the degree of 'archival science Phaleography and Diplomatics' on students passing the exams. This degree authenticates trainees' qualification which enables him to work at the archive in province, district and administrative capital city and archive of comunity and so on. Italian training course naturally leads archivists to keep in contact with valuable cultural inheritance through training in Archive. And it shows the intention to strengthen the affinity with each documents in the spot of archival management before training archivists. Also this is appraised as one of positive policies to conserve the local cultual inheritante in connection with the original qualitity of national archive with testify the history of each region. Traning course for archivist in Italy shows us the way how we have to prepare and proceed it. First, from producing documents to conserving than forever there has introduced 'original order that is to say a general rule to respect the first order given at the time producing documents'. Management of administrative documents is related consistently with one of historical documents. Second, the traning course for archivist is managing around 17 national archives. because italian national archive lay stress not or rducation of theory bus on train for archivest working in the first time of archival science. Third, diplomatics and phaleography for studies about historical document support archives. Forth, the studies on history id proceeding by cooperation between archivist and historian around archive. How our duties is non continuinf disputer who has to conserve and manage document and archives, but traing experts who having ability, vision and flexible thought, responsibility about archivals.