Purpose: This study aims to explore whether content originality and user experience have positive effects on online news readers’ satisfaction with the mobile apps service.Design/methodology/approach: Data was collec...Purpose: This study aims to explore whether content originality and user experience have positive effects on online news readers’ satisfaction with the mobile apps service.Design/methodology/approach: Data was collected via a Web-based survey. Data analysis of this study can be divided into two stages. In the first stage, a descriptive statistical analysis was conducted based on a sample of 612 respondents. In the second stage, the correlation among content originality, user experience and satisfaction was analyzed based on a sample of 377 mobile news apps users. Findings: Results of the first stage showed that social media and mobile news apps were the most important tools for users to access news, and different types of media were playing complementary roles in information transmission. Users held a positive attitude toward their mobile news reading experience and they described news they read on mobile apps with such words as "interesting", "instant", "positive", "profound", and "ironic". Results of the second stage confirmed our hypothesis that content originality and user experience both had positive impacts on user satisfaction.Research limitations: The questionnaires were distributed entirely online, so the sample may not be representative of the general population being studied and thus undermine the reliability and generalization of the findings to some extent. Moreover, this study adopted only one method(survey) and more methods such as interviews can be used to improve the accuracy of the results.Practical implications: The findings of this study can not only provide insights into a better understanding of users’ mobile reading behavior, but also help mobile information service providers attract more users.Originality/value: This is one of the first studies to explore the effects of content originality and user experience on online news readers’ satisfaction with the mobile apps service.展开更多
Objective: This study was conducted to explore what media exactly do when disease is emerging and furthermore, to infer the role and the responsibility that media should play. Method: A content analysis with 0.81 inte...Objective: This study was conducted to explore what media exactly do when disease is emerging and furthermore, to infer the role and the responsibility that media should play. Method: A content analysis with 0.81 inter-rater reliability was adopted to categorize SARS-related events shown on the three major newspapers in 117 days, dated from March 13th (the date before the first probable case of SARS in Taiwan was identified) to July 7th (the date after Taiwan was removed from the list of SARS-affected countries by the bulletin of World Health Organization), 2003. Results: There were totally 8923 SARS events related news found in the observed newspapers during the study period. When the epidemic situation is more serious, the media will also lay out more coverage on reporting the related contents. In the reporting contents, the three most influential newspapers in Taiwan mainly emphasized the impact dimension (34.27%). Only 2.16% of the coverage was on the topic of health communication and prevention education. Overall, the opinions of general public are the primary sources of news (46.57%). Health authority was not the main and typical sources information of the press (9.42%). Conclusion: Media is a double-edged sword in the communicable disease control. We suggest that the health authority should take advantage of media to transmit message rapidly to convey related information to public.展开更多
A schema for content-based analysis of broadcast news video is presented. First, we separate commercials from news using audiovisual features. Then, we automatically organize news programs into a content hierarchy at ...A schema for content-based analysis of broadcast news video is presented. First, we separate commercials from news using audiovisual features. Then, we automatically organize news programs into a content hierarchy at various levels of abstraction via effective integration of video, audio, and text data available from the news programs. Based on these news video structure and content analysis technologies, a TV news video Library is generated, from which users can retrieve definite news story according to their demands.展开更多
Online news recommendation systems aim to address the information explosion of news and make personalized recommendations for users. The key problem of personalized news recommendation is to model users' interests...Online news recommendation systems aim to address the information explosion of news and make personalized recommendations for users. The key problem of personalized news recommendation is to model users' interests and track their changes. A common way to deal with the user modeling problem is to build user profiles from observed behavior. However, the majority of existing methods make static representations of user profiles and little research has focused on effective user modeling that could dynamically capture user interests in news topics. To address this problem, in this paper, we propose UP-TreeRec, a news recommendation framework based on a user profile tree(UP-Tree), which is a novel framework combining content-based and collaborative filtering techniques. First, by exploiting a novel topic model namely UILDA, we obtain the representation vectors for news content in a topic space as the fundamental bridge to associate user interests with news topics. Next, we design a decision tree with a dynamically changeable structure to construct a user interest profile from the user's feedback. Furthermore, we present a clustering-based multidimensional similarity computation method to select the nearest neighbor of the UP-Tree efficiently. We also provide a Map-Reduce framework-based implemen-tation that enables scaling our solution to real-world news recommendation problems. We conducted several experiments compared to the state-of-the-art approaches on real-world datasets and the experimental results demonstrate that our approach significantly improves accuracy and effectiveness in news recommendation.展开更多
This paper attempts to evaluate New Horizon College English(Reading and Writing,Book I, Second Edition) based on the textbook evaluation criteria by Hutchinson& Waters. The analyses proves that that it is fit for ...This paper attempts to evaluate New Horizon College English(Reading and Writing,Book I, Second Edition) based on the textbook evaluation criteria by Hutchinson& Waters. The analyses proves that that it is fit for college students under the circumstances of so many newly published English teaching materials claimed to be excellent and helpful.However, teachers should be aware to take good advantage of the textbook and supplement the students with some necessary resources during teaching due to its limitations.展开更多
For news video images, caption recognizing is a useful and important step for content understanding. Caption locating is usually the first step of caption recognizing and this paper proposes a simple but effective cap...For news video images, caption recognizing is a useful and important step for content understanding. Caption locating is usually the first step of caption recognizing and this paper proposes a simple but effective caption locating algorithm called maximum feature score region （MFSR） based method, which mainly consists of two stages： In the first stage, up/down boundaries are attained by turning to edge map projection. Then, maximum feature score region is defined and left/right boundaries are achieved by utilizing MFSR. Experiments show that the proposed MFSR based method has superior and robust performance on news video images of different types.展开更多
文摘Purpose: This study aims to explore whether content originality and user experience have positive effects on online news readers’ satisfaction with the mobile apps service.Design/methodology/approach: Data was collected via a Web-based survey. Data analysis of this study can be divided into two stages. In the first stage, a descriptive statistical analysis was conducted based on a sample of 612 respondents. In the second stage, the correlation among content originality, user experience and satisfaction was analyzed based on a sample of 377 mobile news apps users. Findings: Results of the first stage showed that social media and mobile news apps were the most important tools for users to access news, and different types of media were playing complementary roles in information transmission. Users held a positive attitude toward their mobile news reading experience and they described news they read on mobile apps with such words as "interesting", "instant", "positive", "profound", and "ironic". Results of the second stage confirmed our hypothesis that content originality and user experience both had positive impacts on user satisfaction.Research limitations: The questionnaires were distributed entirely online, so the sample may not be representative of the general population being studied and thus undermine the reliability and generalization of the findings to some extent. Moreover, this study adopted only one method(survey) and more methods such as interviews can be used to improve the accuracy of the results.Practical implications: The findings of this study can not only provide insights into a better understanding of users’ mobile reading behavior, but also help mobile information service providers attract more users.Originality/value: This is one of the first studies to explore the effects of content originality and user experience on online news readers’ satisfaction with the mobile apps service.
文摘Objective: This study was conducted to explore what media exactly do when disease is emerging and furthermore, to infer the role and the responsibility that media should play. Method: A content analysis with 0.81 inter-rater reliability was adopted to categorize SARS-related events shown on the three major newspapers in 117 days, dated from March 13th (the date before the first probable case of SARS in Taiwan was identified) to July 7th (the date after Taiwan was removed from the list of SARS-affected countries by the bulletin of World Health Organization), 2003. Results: There were totally 8923 SARS events related news found in the observed newspapers during the study period. When the epidemic situation is more serious, the media will also lay out more coverage on reporting the related contents. In the reporting contents, the three most influential newspapers in Taiwan mainly emphasized the impact dimension (34.27%). Only 2.16% of the coverage was on the topic of health communication and prevention education. Overall, the opinions of general public are the primary sources of news (46.57%). Health authority was not the main and typical sources information of the press (9.42%). Conclusion: Media is a double-edged sword in the communicable disease control. We suggest that the health authority should take advantage of media to transmit message rapidly to convey related information to public.
基金Supported by the Science Item of National Power Company( No.SPKJ0 16 -0 71)
文摘A schema for content-based analysis of broadcast news video is presented. First, we separate commercials from news using audiovisual features. Then, we automatically organize news programs into a content hierarchy at various levels of abstraction via effective integration of video, audio, and text data available from the news programs. Based on these news video structure and content analysis technologies, a TV news video Library is generated, from which users can retrieve definite news story according to their demands.
基金supported by the Beijing Natural Science Foundation (No.4192008)the General Project of Beijing Municipal Education Commission (No. KM201710005023)
文摘Online news recommendation systems aim to address the information explosion of news and make personalized recommendations for users. The key problem of personalized news recommendation is to model users' interests and track their changes. A common way to deal with the user modeling problem is to build user profiles from observed behavior. However, the majority of existing methods make static representations of user profiles and little research has focused on effective user modeling that could dynamically capture user interests in news topics. To address this problem, in this paper, we propose UP-TreeRec, a news recommendation framework based on a user profile tree(UP-Tree), which is a novel framework combining content-based and collaborative filtering techniques. First, by exploiting a novel topic model namely UILDA, we obtain the representation vectors for news content in a topic space as the fundamental bridge to associate user interests with news topics. Next, we design a decision tree with a dynamically changeable structure to construct a user interest profile from the user's feedback. Furthermore, we present a clustering-based multidimensional similarity computation method to select the nearest neighbor of the UP-Tree efficiently. We also provide a Map-Reduce framework-based implemen-tation that enables scaling our solution to real-world news recommendation problems. We conducted several experiments compared to the state-of-the-art approaches on real-world datasets and the experimental results demonstrate that our approach significantly improves accuracy and effectiveness in news recommendation.
文摘This paper attempts to evaluate New Horizon College English(Reading and Writing,Book I, Second Edition) based on the textbook evaluation criteria by Hutchinson& Waters. The analyses proves that that it is fit for college students under the circumstances of so many newly published English teaching materials claimed to be excellent and helpful.However, teachers should be aware to take good advantage of the textbook and supplement the students with some necessary resources during teaching due to its limitations.
基金supported by National Natural Science Foundation of China(Nos.61272394,61201395 and61472119)the program for Science&Technology Innovation Talents in Universities of Henan Province(No.13HASTIT039)+1 种基金Henan Polytechnic University Innovative Research Team(No.T2014-3)Henan Polytechnic University Fund for Distinguished Young Scholars(No.J2013-2)
文摘For news video images, caption recognizing is a useful and important step for content understanding. Caption locating is usually the first step of caption recognizing and this paper proposes a simple but effective caption locating algorithm called maximum feature score region （MFSR） based method, which mainly consists of two stages： In the first stage, up/down boundaries are attained by turning to edge map projection. Then, maximum feature score region is defined and left/right boundaries are achieved by utilizing MFSR. Experiments show that the proposed MFSR based method has superior and robust performance on news video images of different types.
