標(biāo)題: Titlebook: Recommender Systems for the Social Web; José J. Pazos Arias,Ana Fernández Vilas,Rebeca P. Book 2012 Springer-Verlag GmbH Berlin Heidelber [打印本頁] 作者: 古生物學(xué) 時間: 2025-3-21 18:15
書目名稱Recommender Systems for the Social Web影響因子(影響力)
書目名稱Recommender Systems for the Social Web影響因子(影響力)學(xué)科排名
書目名稱Recommender Systems for the Social Web網(wǎng)絡(luò)公開度
書目名稱Recommender Systems for the Social Web網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Recommender Systems for the Social Web被引頻次
書目名稱Recommender Systems for the Social Web被引頻次學(xué)科排名
書目名稱Recommender Systems for the Social Web年度引用
書目名稱Recommender Systems for the Social Web年度引用學(xué)科排名
書目名稱Recommender Systems for the Social Web讀者反饋
書目名稱Recommender Systems for the Social Web讀者反饋學(xué)科排名
作者: minaret 時間: 2025-3-21 23:56
Augmenting Collaborative Recommenders by Fusing Social Relationships: Membership and Friendshipand dense datasets as obtained from Last.fm. Our experiments have not only revealed the significant effects of the two relationships, especially the membership, in augmenting recommendation accuracy in the sparse data condition, but also identified the outperforming ability of the graph modeling in terms of realizing the optimal fusion mechanism.作者: engrossed 時間: 2025-3-22 01:56 作者: SPER 時間: 2025-3-22 05:16
Social Recommender Systemsems in the basic landscape of recommender systems in general via a short review and comparison, we present related work in this more specialized area. After having laid out the basic conceptual grounds, we then contrast an earlier study with a recent study in order to investigate the limits of appli作者: endarterectomy 時間: 2025-3-22 11:10 作者: 大看臺 時間: 2025-3-22 15:21
Challenges in Tag Recommendations for Collaborative Tagging Systemswikis, e-commerce platforms, or social networks. Collaborative tagging systems allow users to annotate resources using freely chosen keywords, so called .. Those tags help users in finding/retrieving resources, discovering new resources, and navigating through the system..The process of tagging reso作者: fiction 時間: 2025-3-22 19:45
A Multi-criteria Approach for Automatic Ontology Recommendation Using Collective Knowledged processing of information are critical issues (e.g. biomedicine). In these domains, the number of available ontologies has grown rapidly during the last years. This is very positive because it enables a more effective (or more intelligent) knowledge management. However, it raises a new problem: wh作者: glans-penis 時間: 2025-3-22 23:32
Implicit Trust Networks: A Semantic Approach to Improve Collaborative Recommendationse main concern in a collaborative recommendation is to identify the most suitable set of users to drive the selection of the items to be offered in each case. To distinguish relevant and reliable users from unreliable ones, trust and reputation models are being increasingly incorporated in these sys作者: CHOKE 時間: 2025-3-23 01:37
Social Recommendation Based on a Rich Aggregation Modelmodel. The underlying infrastructure is based on a complex relationship model among three core entities: people, items, and tags. We describe the general model and the different recommender systems that were built on top, including the main results and the implications from one system to another. We作者: Boycott 時間: 2025-3-23 08:45
Group Recommender Systems: New Perspectives in the Social Webr, we revise state of the art approaches on group formation, modelling and recommendation, and present challenging problems to be included in the group recommender system research agenda in the context of the Social Web.作者: WAX 時間: 2025-3-23 13:26 作者: 隱藏 時間: 2025-3-23 17:04
Recommendations on the Movein. Taking a step further, these suggestions could be based not only on the user’s current location, but also on the places where the user is supposed to be in the near future, so the recommended locations would be on the path the user is going to follow. In order to do that we need some location pr作者: FOLD 時間: 2025-3-23 19:29 作者: 花束 時間: 2025-3-24 01:02
Conclusiones and Open Trends, their legal effects, the problem of interoperability and the social influence for recommendation (trust and groups). Finally, two differentes applications of social recommendation are also shown. This chapter include the authors’ view about the open trends and the future of recommendation. Specifi作者: linguistics 時間: 2025-3-24 03:44
Social Recommendation Based on a Rich Aggregation Modelral model and the different recommender systems that were built on top, including the main results and the implications from one system to another. We conclude by highlighting the main findings and suggesting next steps and future directions.作者: gospel 時間: 2025-3-24 09:15
1868-4394 e Web 2.0 hype which have to be incorporated in traditional .The recommendation of products, content and services cannot be considered newly born, although its widespread application is still in full swing. While its growing success in numerous sectors, the progress of the ?Social Web has revolution作者: 北極人 時間: 2025-3-24 10:40
Implicit Trust Networks: A Semantic Approach to Improve Collaborative Recommendationso provide explicit data (about which other users they trust or not) to form such networks. In this chapter, we apply a semantic approach to automatically build implicit trust networks and, thereby, improve the recommendation results transparently to the users.作者: 讓空氣進(jìn)入 時間: 2025-3-24 16:14
SCORM and Social Recommendation: A Web 2.0 Approach to E-learningeducative content that are not able to filter, asses and/or consume. Along this line, we introduce in this paper a new recommendation mechanism supported by the tag clouds which label both users and content.作者: 難聽的聲音 時間: 2025-3-24 22:50 作者: 令人苦惱 時間: 2025-3-25 01:21 作者: 不開心 時間: 2025-3-25 04:18 作者: LAIR 時間: 2025-3-25 11:33 作者: Agility 時間: 2025-3-25 14:19 作者: appall 時間: 2025-3-25 17:57
Group Recommender Systems: New Perspectives in the Social Webr, we revise state of the art approaches on group formation, modelling and recommendation, and present challenging problems to be included in the group recommender system research agenda in the context of the Social Web.作者: Progesterone 時間: 2025-3-25 21:06
Intelligent Systems Reference Libraryhttp://image.papertrans.cn/r/image/824132.jpg作者: accomplishment 時間: 2025-3-26 03:01 作者: defendant 時間: 2025-3-26 05:06
Manuela I. Martín-Vicente,Alberto Gil-Solla,Manuel Ramos-Cabrere demonstrated that single sequence variants predictive of common human disease are rare. Instead, disease risk is thought to be the result of a confluence of many genes acting in concert, often with no statistically significant individual effects. The detection and characterization of such gene-gen作者: 可卡 時間: 2025-3-26 10:45
Ido Guylgorithms (EDAs). Distribution Estimation Using Markov network (DEUM) is one of the early EDAs to use this approach. Over the years, several different versions of DEUM have been proposed using different Markov network structures, and are shown to work well in a number of different optimisation probl作者: 男生如果明白 時間: 2025-3-26 16:21
e demonstrated that single sequence variants predictive of common human disease are rare. Instead, disease risk is thought to be the result of a confluence of many genes acting in concert, often with no statistically significant individual effects. The detection and characterization of such gene-gen作者: THE 時間: 2025-3-26 17:28 作者: 大暴雨 時間: 2025-3-26 23:35
Quan Yuan,Li Chen,Shiwan Zhaoe demonstrated that single sequence variants predictive of common human disease are rare. Instead, disease risk is thought to be the result of a confluence of many genes acting in concert, often with no statistically significant individual effects. The detection and characterization of such gene-gen作者: 先行 時間: 2025-3-27 02:24
el parameter estimates and structures that can in principle be reduced over time, and persistent changes in parameters and structure due to a host of possible factors that are mostly unpredictable even in principle. Thus we must learn to live with continuing uncertainty as a basic feature of fisheri作者: 殺子女者 時間: 2025-3-27 07:48 作者: 感情脆弱 時間: 2025-3-27 12:33 作者: MARS 時間: 2025-3-27 16:56 作者: coagulation 時間: 2025-3-27 20:12 作者: preeclampsia 時間: 2025-3-28 00:30
Social Recommender Systemsn boards. While the former study showed that the social filtering approach works very well in taste related domains, the second study shows that a mere transplantation of the idea to a more factual domain and a situation with sparse social network data does perform less satisfactorially.作者: CLOWN 時間: 2025-3-28 02:47 作者: 褪色 時間: 2025-3-28 09:22
Challenges in Tag Recommendations for Collaborative Tagging Systemsk and publication sharing system BibSonomy. Moreover, the 2009 challenge included an online task where the recommender systems were integrated into BibSonomy and provided recommendations in real time..In this chapter we review, evaluate and summarize the submissions to the two Discovery Challenges a作者: Guileless 時間: 2025-3-28 13:53 作者: SHRIK 時間: 2025-3-28 18:02
Robert J?schke,Andreas Hotho,Folke Mitzlaff,Gerd Stumme作者: 浮雕 時間: 2025-3-28 21:09 作者: pancreas 時間: 2025-3-29 02:00 作者: 密切關(guān)系 時間: 2025-3-29 04:22 作者: 存心 時間: 2025-3-29 08:34 作者: echnic 時間: 2025-3-29 14:27 作者: Diskectomy 時間: 2025-3-29 15:41
Iván Cantador,Pablo Castellsin the population. We complete the analysis by calculating the position of the optimum in the . MPSs during the search and the genotypic diversity of these solutions. We carry out the analysis by optimizing functions of different natures such as Trap5, two variants of Ising spin glass and Max-SAT. T
