Browsing by Author "Chiu, Po-Huan"

Now showing 1 - 4 of 4

Integrating Semantic Web and Object-Oriented Programming for Cooperative Design
(2009)
Chiu, Po-Huan
;
Lo, Chi-Chun
;
Chao, Kuo-Ming
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Object-oriented programming (OOP) is a mainstream paradigm for engineering design software tool development. An emerging requirement is the introduction of semantics to achieve heterogeneous information sharing, but many challenges exist. Examples include using object methods to manipulate an RDF data, automatically converting data into RDF format, and supporting various programming languages. In addition, limitations to description capabilities for relationships among object-oriented classes exceed those of RDF, thus hindering direct mapping between object-oriented and Semantic Web classes. Our proposed semantic object framework (SOF) combines object-oriented design and Semantic Web features. SOF utilizes embedded comments in source code to describe semantic relationships between classes and attributes. We use a mobile phone design case study to illustrate how the proposed system operates.
Personalized blog content recommender system for mobile phone users
(2010-08-01)
Chiu, Po-Huan
;
Kao, Gloria Yi-Min
;
Lo, Chi-Chun
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Compared to newspaper columnists and broadcast media commentators, bloggers do not have organizations actively promoting their content to users; instead, they rely on word-of-mouth or casual visits by web surfers. We believe the WAP Push service feature of mobile phones can help bridge the gap between internet and mobile services, and expand the number of potential blog readers. Since mobile phone screen size is very limited, content providers must be familiar with individual user preferences in order to recommend content that matches narrowly defined personal interests. To help identify popular blog topics, we have created (a) an information retrieval process that clusters blogs into groups based on keyword analyses, and (b) a mobile content recommender system (M-CRS) for calculating user preferences for new blog documents. Here we describe results from a case study involving 20,000 mobile phone users in which we examined the effects of personalized content recommendations. Browsing habits and user histories were recorded and analyzed to determine individual preferences for making content recommendations via the WAP Push feature. The evaluation results of our recommender system indicate significant increases in both blog-related push service click rates and user time spent reading personalized web pages. The process used in this study supports accurate recommendations of personalized mobile content according to user interests. This approach can be applied to other embedded systems with device limitations, since document subject lines are elaborated and more attractive to intended users. (C) 2010 Elsevier Ltd. All rights reserved.
Personalized recommendation of popular blog articles for mobile applications
(2011-05-01)
Liu, Duen-Ren
;
Tsai, Pei-Yun
;
Chiu, Po-Huan
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Weblogs have emerged as a new communication and publication medium on the Internet for diffusing the latest useful information. Providing value-added mobile services, such as blog articles, is increasingly important to attract mobile users to mobile commerce, in order to benefit from the proliferation and convenience of using mobile devices to receive information any time and anywhere. However, there are a tremendous number of blog articles, and mobile users generally have difficulty in browsing weblogs owing to the limitations of mobile devices. Accordingly, providing mobile users with blog articles that suit their particular interests is an important issue. Very little research, however, has focused on this issue. In this work, we propose a novel Customized Content Service on a mobile device (m-CCS) to filter and push blog articles to mobile users. The m-CCS includes a novel forecasting approach to predict the latest popular blog topics based on the trend of time-sensitive popularity of weblogs. Mobile users may, however, have different interests regarding the latest popular blog topics. Thus, the m-CCS further analyzes the mobile users' browsing logs to determine their interests, which are then combined with the latest popular blog topics to derive their preferred blog topics and articles. A novel hybrid approach is proposed to recommend blog articles by integrating personalized popularity of topic clusters, item-based collaborative filtering (CF) and attention degree (click times) of blog articles. The experiment result demonstrates that the m-CCS system can effectively recommend mobile users' desired blog articles with respect to both popularity and personal interests. (C) 2011 Elsevier Inc. All rights reserved.
Recommending quality book reviews from heterogeneous websites
(2013)
Liu, Duen-Ren
;
Chen, Nei-Hsiao
;
Chiu, Po-Huan
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Purpose - In recent years, readers have limited amounts of time to pick the right books to read from a market that is filled with similar types of books. Aiming to read only good books, readers tend to check book reviews written by others. However, it is very difficult to find good book reviews. The aim of this paper is to present a book review recommendation system that collects reviews from heterogeneous sources on the Internet and performs quality judgments automatically. Users can then read the top-ranked reviews suggested by this recommendation system. Design/methodology/approach - In this paper, a book review recommendation system is constructed to collect, process, and judge the quality of book reviews from various heterogeneous sources. The quality measurement of book reviews uses review-evaluation techniques. The prediction results were validated with a ranking list produced by experts. Findings - The proposed system is effective and suitable for recommending quality book reviews from heterogeneous sources. The proposed quality measurement method is more effective than other more commonly used methods. Originality/value - This paper is one of the first to apply review evaluation techniques to the process of book review recommendation. The proposed system can collect and recognize book reviews from different websites with various forms of presentation. This evaluation shows that the quality measurement method produces better results than-do other methods, such as ranking by rating score or by the date that the review was posted. Those methods are primarily used by commercial websites.