排序方式: 共有34条查询结果,搜索用时 15 毫秒
31.
Sajad Ahmadian Majid Meghdadi Mohsen Afsharchi 《Information processing & management》2018,54(4):707-725
Recommender systems are techniques to make personalized recommendations of items to users. In e-commerce sites and online sharing communities, providing high quality recommendations is an important issue which can help the users to make effective decisions to select a set of items. Collaborative filtering is an important type of the recommender systems that produces user specific recommendations of the items based on the patterns of ratings or usage (e.g. purchases). However, the quality of predicted ratings and neighbor selection for the users are important problems in the recommender systems. Selecting suitable neighbors set for the users leads to improve the accuracy of ratings prediction in recommendation process. In this paper, a novel social recommendation method is proposed which is based on an adaptive neighbor selection mechanism. In the proposed method first of all, initial neighbors set of the users is calculated using clustering algorithm. In this step, the combination of historical ratings and social information between the users are used to form initial neighbors set for the users. Then, these neighbor sets are used to predict initial ratings of the unseen items. Moreover, the quality of the initial predicted ratings is evaluated using a reliability measure which is based on the historical ratings and social information between the users. Then, a confidence model is proposed to remove useless users from the initial neighbors of the users and form a new adapted neighbors set for the users. Finally, new ratings of the unseen items are predicted using the new adapted neighbors set of the users and the interested items are recommended to the active user. Experimental results on three real-world datasets show that the proposed method significantly outperforms several state-of-the-art recommendation methods. 相似文献
32.
Payam Hanafizadeh Mohammad Reza Hanafizadeh Mohsen Khodabakhshi 《The Information Society》2013,29(4):236-247
In this article a methodology is presented to extract indicators that appropriately measure the information society and the digital divide between countries and the relevant statistics that the majority of countries can collect. With the help of content analysis, the entropy method, and consideration of the diffusion aspects of digitalization, 37 reputable information society and digital divide models are analyzed to indentify “core information and communication technology (ICT) indicators.” To overcome the limitation of the nonexistence of data, the information and the knowledge embedded in information society and digital divide models are employed as proxies for experts' opinions for extracting the core ICT indicators. Comparison of the prior indicators and the proposed ones reveals that the former ignore three important dimensions: e-learning, e-government, and networked world enablers. 相似文献
33.
Fattane Zarrinkalam Mohsen Kahani Ebrahim Bagheri 《Information processing & management》2018,54(2):339-357
Inferring users’ interests from their activities on social networks has been an emerging research topic in the recent years. Most existing approaches heavily rely on the explicit contributions (posts) of a user and overlook users’ implicit interests, i.e., those potential user interests that the user did not explicitly mention but might have interest in. Given a set of active topics present in a social network in a specified time interval, our goal is to build an interest profile for a user over these topics by considering both explicit and implicit interests of the user. The reason for this is that the interests of free-riders and cold start users who constitute a large majority of social network users, cannot be directly identified from their explicit contributions to the social network. Specifically, to infer users’ implicit interests, we propose a graph-based link prediction schema that operates over a representation model consisting of three types of information: user explicit contributions to topics, relationships between users, and the relatedness between topics. Through extensive experiments on different variants of our representation model and considering both homogeneous and heterogeneous link prediction, we investigate how topic relatedness and users’ homophily relation impact the quality of inferring users’ implicit interests. Comparison with state-of-the-art baselines on a real-world Twitter dataset demonstrates the effectiveness of our model in inferring users’ interests in terms of perplexity and in the context of retweet prediction application. Moreover, we further show that the impact of our work is especially meaningful when considered in case of free-riders and cold start users. 相似文献
34.
Masoud Kabiri Mahmood Ghazi-Tabatabaei Abbas Bazargan Mohsen Shokoohi-Yekta Kamal Kharrazi 《教育实用测度》2017,30(1):27-38
Numerous diagnostic studies have been conducted on large-scale assessments to illustrate the students’ mastery profile in the areas of math and reading; however, for science a limited number of investigations are reported. This study investigated Iranian eighth graders’ competency mastery of science and examined the utility of the General Diagnostic Model (GDM) to produce diagnostic information using TIMSS 2011 data. Eight diagnostic attributes were extracted, using documentary analysis of the major large-scale assessment frameworks, including basic science knowledge, using models, reasoning, using science, representing data, explaining of phenomena, predicting, and scientific inquiry. These attributes were then assigned to each item in order to construct the Q matrix, through focus group discussions, survey of head science teachers, think-aloud verbal protocol, and analysis of written answers. Results show the utility of GDM to generate rich diagnostic information for a national large-scale assessment. Moreover, the findings indicated that students performed relatively well in using science, but performed weakly in reasoning, explaining of phenomena, and scientific inquiry, which all required complex skills and higher-order thinking abilities. 相似文献