Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web最新文献

{"title":"Session details: Recommender applications for the social web","authors":"A. Hotho","doi":"10.1145/3251594","DOIUrl":"https://doi.org/10.1145/3251594","url":null,"abstract":"","PeriodicalId":258534,"journal":{"name":"Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web","volume":"281 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127553512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web","authors":"B. Mobasher, D. Jannach, Werner Geyer, A. Hotho","doi":"10.1145/2365934","DOIUrl":"https://doi.org/10.1145/2365934","url":null,"abstract":"The new opportunities for applying recommendation techniques within Social Web platforms and applications as well as the various new sources of information which have become available in the Web 2.0 and can be incorporated in future recommender applications are a strong driving factor in current recommender system research for various reasons: \u0000 \u0000(1) Social systems by their definition encourage interaction between users and both online content and other users, thus generating new sources of knowledge for recommender systems. Web 2.0 users explicitly provide personal information and implicitly express preferences through their interactions with others and the system (e.g. commenting, friending, rating, etc.). These various new sources of knowledge can be leveraged to improve recommendation techniques and develop new strategies which focus on social recommendation. \u0000 \u0000(2) New application areas for recommender systems emerge with the popularity of the Social Web. Recommenders cannot only be used to sort and filter Web 2.0 and social network information, they can also support users in the information sharing process, e.g., by recommending suitable tags during folksonomy development. \u0000 \u0000(3) Recommender technology can assist Social Web systems through increasing adoption and participation and sustaining membership. Through targeted and timely intervention which stimulates traffic and interaction, recommender technology can play its role in sustaining the success of the Social Web. \u0000 \u0000(4) The Social Web also presents new challenges for recommender systems, such as the complicated nature of human-to-human interaction which comes into play when recommending people and can require more interactive and richer recommender systems user interfaces. \u0000 \u0000The technical papers appearing in these proceedings aim to explore and understand challenges and new opportunities for recommender systems in the Social Web and were selected in a formal review process by an international program committee. \u0000 \u0000Overall, we received 13 paper submissions from 12 different countries, out of which 7 long papers and 1 short paper were selected for presentation and inclusion in the proceedings. The submitted papers addressed a variety of topics related to Social Web recommender systems from the use of microblogging data for personalization over new tag recommendation approaches to social media-based personalization of news.","PeriodicalId":258534,"journal":{"name":"Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129409153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging publication metadata and social data into FolkRank for scientific publication recommendation","authors":"Stephan Doerfel, R. Jäschke, A. Hotho, Gerd Stumme","doi":"10.1145/2365934.2365937","DOIUrl":"https://doi.org/10.1145/2365934.2365937","url":null,"abstract":"The ever-growing flood of new scientific articles requires novel retrieval mechanisms. One means for mitigating this instance of the information overload phenomenon are collaborative tagging systems, that allow users to select, share and annotate references to publications. These systems employ recommendation algorithms to present to their users personalized lists of interesting and relevant publications. In this paper we analyze different ways to incorporate social data and metadata from collaborative tagging systems into the graph-based ranking algorithm FolkRank to utilize it for recommending scientific articles to users of the social bookmarking system BibSonomy. We compare the results to those of Collaborative Filtering, which has previously been applied for resource recommendation.","PeriodicalId":258534,"journal":{"name":"Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133583659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Online dating recommender systems: the split-complex number approach","authors":"Jérôme Kunegis, Gerd Gröner, Thomas Gottron","doi":"10.1145/2365934.2365942","DOIUrl":"https://doi.org/10.1145/2365934.2365942","url":null,"abstract":"A typical recommender setting is based on two kinds of relations: similarity between users (or between objects) and the taste of users towards certain objects. In environments such as online dating websites, these two relations are difficult to separate, as the users can be similar to each other, but also have preferences towards other users, i.e., rate other users. In this paper, we present a novel and unified way to model this duality of the relations by using split-complex numbers, a number system related to the complex numbers that is used in mathematics, physics and other fields. We show that this unified representation is capable of modeling both notions of relations between users in a joint expression and apply it for recommending potential partners. In experiments with the Czech dating website Libimseti.cz we show that our modeling approach leads to an improvement over baseline recommendation methods in this scenario.","PeriodicalId":258534,"journal":{"name":"Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web","volume":"167 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132293201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FReSET: an evaluation framework for folksonomy-based recommender systems","authors":"R. García, Matthias Bender, Mojisola Erdt, Christoph Rensing, R. Steinmetz","doi":"10.1145/2365934.2365939","DOIUrl":"https://doi.org/10.1145/2365934.2365939","url":null,"abstract":"FReSET is a new recommender systems evaluation framework aiming to support research on folksonomy-based recommender systems. It provides interfaces for the implementation of folksonomy-based recommender systems and supports the consistent and reproducible offline evaluations on historical data. Unlike other recommender systems framework projects, the emphasis here is on providing a flexible framework allowing users to implement their own folksonomy-based recommender algorithms and pre-processing filtering methods rather than just providing a collection of collaborative filtering implementations. FReSET includes a graphical interface for result visualization and different cross-validation implementations to complement the basic functionality.","PeriodicalId":258534,"journal":{"name":"Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121026062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social media-driven news personalization","authors":"S. O’Banion, L. Birnbaum, K. Hammond","doi":"10.1145/2365934.2365943","DOIUrl":"https://doi.org/10.1145/2365934.2365943","url":null,"abstract":"While social media have achieved significant and widespread adoption as platforms for sharing information, their use as a source of data for predicting user interests has not yet been fully explored. In this paper, we present a content-based approach to modeling user interests based on Twitter. Our recommendation system uses information retrieval techniques to represent tweets and users as collections of news topics, including high-level categories (e.g., sports, politics, business) and detailed subtopics (e.g., Chicago Bulls, Mitt Romney, entrepreneurship). We discuss the design of a system that uses this information to deliver news recommendations in the form of a personalized newspaper. Finally, we describe a novel method for evaluating recommendation systems based on Twitter that involves mining Twitter data to identify explicit indicators of news interests and comparing these to retroactive system recommendations.","PeriodicalId":258534,"journal":{"name":"Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127548902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trust-based local and social recommendation","authors":"Simon Meyffret, L. Médini, F. Laforest","doi":"10.1145/2365934.2365945","DOIUrl":"https://doi.org/10.1145/2365934.2365945","url":null,"abstract":"In this article, we propose an evolution of trust-based recommender systems that only relies on local information and can be deployed on top of existing social networks. Our approach takes into account friends' similarity and confidence on ratings, but limits data exchange to direct friends, in order to prevent ratings from being globally known. Therefore, calculations are limited to locally processed algorithms, privacy concerns can be taken into account and algorithms are suitable for decentralized or peer-to-peer architectures. We have implemented and evaluated our approach against five others, using the Epinions trust network. We show that local information with good default scoring strategies are sufficient to cover more users than classical collaborative filtering and trust-based recommender systems. Regarding accuracy, our approach performs better than most others, specially for cold start users, despite using less information.","PeriodicalId":258534,"journal":{"name":"Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121594569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Context determines content: an approach to resource recommendation in folksonomies","authors":"T. Rodenhausen, Mojisola Erdt, R. García, Christoph Rensing","doi":"10.1145/2365934.2365938","DOIUrl":"https://doi.org/10.1145/2365934.2365938","url":null,"abstract":"By means of tagging in social bookmarking applications, so called folksonomies emerge collaboratively. Folksonomies have shown to contain information that is beneficial for resource recommendation. However, as folksonomies are not designed to support recommendation tasks, there are drawbacks of the various recommendation techniques. Graph-based recommendation in folksonomies for example suffers from the problem of concept drift. Vector space based recommendation approaches in folksonomies suffer from sparseness of available data. In this paper, we propose the flexible framework VSScore which incorporates context-specific information into the recommendation process to tackle these issues. Additionally, as an alternative to the evaluation methodology LeavePostOut we propose an adaptation LeaveRTOut for resource recommendation in folksonomies. In a subset of resource recommendation tasks evaluated, the proposed recommendation framework VSScore performs significantly more effective than the baseline algorithm FolkRank.","PeriodicalId":258534,"journal":{"name":"Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127060751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Session details: Trust-based recommendations","authors":"D. Jannach","doi":"10.1145/3251595","DOIUrl":"https://doi.org/10.1145/3251595","url":null,"abstract":"","PeriodicalId":258534,"journal":{"name":"Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web","volume":"447 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125773284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Session details: Tags and folksonomies","authors":"B. Mobasher","doi":"10.1145/3251593","DOIUrl":"https://doi.org/10.1145/3251593","url":null,"abstract":"","PeriodicalId":258534,"journal":{"name":"Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130340811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}