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arXiv 2017年

作者： Beierle, Felix Aizawa, Akiko Beel, Joeran Service-centric Networking Technische Universität Berlin Telekom Innovation Laboratories Berlin Germany Digital Content and Media Sciences Research Division Tokyo Japan Trinity College Dublin School of Computer Science and Statistics Intelligent Systems Discipline Knowledge and Data Engineering Group ADAPT Centre Dublin Ireland

We investigate the problem of choice overload – the difficulty of making a decision when faced with many options – when displaying related-article recommendations in digital libraries. So far, research regarding to how many items should be displayed has mostly been done in the fields of media recommendations and search engines. We analyze the number of recommendations in current digital libraries. When browsing fullscreen with a laptop or desktop PC, all display a fixed number of recommendations. 72% display three, four, or five recommendations, none display more than ten. We provide results from an empirical evaluation conducted with GESIS’ digital library Sowiport, with recommendations delivered by recommendations-as-a-service provider Mr. DLib. We use click-through rate as a measure of recommendation effectiveness based on 3.4 million delivered recommendations. Our results show lower click-through rates for higher numbers of recommendations and twice as many clicked recommendations when displaying ten instead of one related-articles. Our results indicate that users might quickly feel overloaded by choice. Copyright © 2017, The Authors. All rights reserved.

关键词： Digital libraries

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Do your social profiles reveal what languages you speak? Language inference from social media profiles 38th

Do your social profiles reveal what languages you speak? Lan...

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38th European Conference on Information Retrieval Research, ECIR 2016

作者： Xu, Yu Ghorab, M. Rami Wang, Zhongqing Zhou, Dong Lawless, Séamus ADAPT Centre Knowledge and Data Engineering Group School of Computer Science and Statistics Trinity College Dublin Dublin Ireland Natural Language Processing Lab Soochow University Suzhou China School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan China

ISBN: (纸本)9783319306704

In the multilingual World Wide Web, it is critical for Web applications, such as multilingual search engines and targeted international advertisements, to know what languages the user understands. However, online users are often unwilling to make the effort to explicitly provide this information. Additionally, language identification techniques struggle when a user does not use all the languages they know to directly interact with the applications. This work proposes a method of inferring the language(s) online users comprehend by analyzing their social profiles. It is mainly based on the intuition that a user’s experiences could imply what languages they know. This is nontrivial, however, as social profiles are usually incomplete, and the languages that are regionally related or similar in vocabulary may share common features;this makes the signals that help to infer language scarce and noisy. This work proposes a language and social relation-based factor graph model to address this problem. To overcome these challenges, it explores external resources to bring in more evidential signals, and exploits the dependency relations between languages as well as social relations between profiles in modeling the problem. Experiments in this work are conducted on a large-scale dataset. The results demonstrate the success of our proposed approach in language inference and show that the proposed framework outperforms several alternative methods. © Springer International Publishing Switzerland 2016.

关键词： Search engines

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Inferring Your Expertise from Twitter: Integrating Sentiment and Topic Relatedness

Inferring Your Expertise from Twitter: Integrating Sentiment...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Yu Xu Dong Zhou Séamus Lawless Knowledge and Data Engineering Group School of Computer Science and Statistics Dublin Ireland School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan China

ISBN: (纸本)9781509044719

The ability to understand the expertise of users in Social Networking Sites (SNSs) is a key component for delivering effective information services such as talent seeking and user recommendation. However, users are often unwilling to make the effort to explicitly provide this information, so existing methods aimed at user expertise discovery in SNSs primarily rely on implicit inference. This work aims to infer a user's expertise based on their posts on the popular micro-blogging site Twitter. The work proposes a sentiment-weighted and topic relation-regularized learning model to address this problem. It first uses the sentiment intensity of a tweet to evaluate its importance in inferring a user's expertise. The intuition is that if a person can forcefully and subjectively express their opinion on a topic, it is more likely that the person has strong knowledge of that topic. Secondly, the relatedness between expertise topics is exploited to model the inference problem. The experiments reported in this paper were conducted on a large-scale dataset with over 10,000 Twitter users and 149 expertise topics. The results demonstrate the success of our proposed approach in user expertise inference and show that the proposed approach outperforms several alternative methods.

关键词： Twitter knowledge discovery Computer languages Sentiment analysis Analytical models

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Defined High Molar Mass Poly(2‐Oxazoline)s

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Angewandte Chemie 2018年第47期130卷

作者： Bryn D. Monnery Valentin V. Jerca Ondrej Sedlacek Bart Verbraeken Rachel Cavill Richard Hoogenboom Supramolecular Chemistry Group Centre of Macromolecular Chemistry (CMaC) Department of Organic and Macromolecular Chemistry Ghent University Krijgslaan 281—S4 9000 Gent Belgium Centre of Organic Chemistry “Costin D. Nenitzescu” Romanian Academy Spl. Independentei 202B 060023 Bucharest Romania Department of Data Science and Knowledge Engineering Maastricht University Bouillonstraat 8–10 6211 LH Maastricht The Netherlands

Poly(2‐alkyl‐2‐oxazoline)s (PAOx) are regaining interest for biomedical applications. However, their full potential is hampered by the inability to synthesise uniform high‐molar mass PAOx. In this work, we proposed alternative intrinsic chain transfer mechanisms based on 2‐oxazoline and oxazolinium chain‐end tautomerisation and derived improved polymerization conditions to suppress chain transfer, allowing the synthesis of highly defined poly(2‐ethyl‐2‐oxazoline)s up to ca. 50 kDa (dispersity ( Ð ) <1.05) and defined polymers up to at least 300 kDa ( Ð <1.2). The determination of the chain transfer constants for the polymerisations hinted towards the tautomerisation of the oxazolinium chain end as most plausible cause for chain transfer. Finally, the method was applied for the preparation of up to 60 kDa molar mass copolymers of 2‐ethyl‐2‐oxazoline and 2‐methoxycarbonylethyl‐2‐oxazoline.

关键词： Kationische Polymerisationen Polymere Ringöffnungspolymerisationen Tautomerisierungen

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knowledge journey exhibit: Towards age-adaptive search user interfaces 37

Knowledge journey exhibit: Towards age-adaptive search user ...

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37th European Conference on Information Retrieval Research, ECIR 2015

作者： Gossen, Tatiana Kotzyba, Michael Nürnberger, Andreas Data and Knowledge Engineering Group Otto von Guericke University Magdeburg Germany

ISBN: (纸本)9783319163536

We describe an information terminal that supports interactive search with an age-adaptable search user interface whose main focus group are young users. The terminal enables a flexible adaptation of the search user interface to address changing requirements of users at different age groups. The interface is operated using touch interactions as they are considered to be more natural for children than using a mouse. Users search within a safe environment;For this purpose a search index was created using a focused crawler. © Springer International Publishing Switzerland 2015.

关键词： User interfaces

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Exploratory subgroup analytics on ubiquitous data 4

Exploratory subgroup analytics on ubiquitous data

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4th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2013 in conjunction with the European Conference on Machine Learning and Principles and Practice of knowledge Discovery in databases, ECML-PKDD 2013

作者： Atzmueller, Martin Mueller, Juergen Becker, Martin Knowledge and Data Engineering Group University of Kassel Kassel Germany Data Mining and Information Retrieval Group University of Würzburg Würzburg Germany

ISBN: (纸本)9783319147222

This paper presents exploratory subgroup analytics on ubiquitous data: We propose subgroup discovery and assessment approaches for obtaining interesting descriptive patterns and provide a novel graphbased analysis approach for assessing the relations between the obtained subgroup set. This exploratory visualization approaches allows for the comparison of subgroups according to their relations to other subgroups and to include further parameters, e.g., geo-spatial distribution indicators. We present and discuss analysis results utilizing real-world data given by geo-tagged noise measurements with associated subjective perceptions and a set of tags describing the semantic context. ©Springer International Publishing Switzerland 2015

关键词： Semantics

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Subgroup and community analytics on attributed graphs

Subgroup and community analytics on attributed graphs

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Workshop on Social Network Analysis using Formal Concept Analysis, SNAFCA 2015

作者： Atzmueller, Martin Knowledge and Data Engineering Group University of Kassel Wilhelmshöher Allee 73 Kassel34121 Germany

Subgroup discovery and community detection are two approaches having been studied in different research areas like data mining and social network analysis. In this context, these techniques are especially helpful in order to provide for analytical and explorative data mining approaches. We present an organized picture of recent research in subgroup discovery and community detection specifically focusing on attributed graphs. That is, we include complex relational graphs that are annotated with additional information, e.g., attribute information on the nodes and/or edges of the graph. In addition, we especially summarize a method combining both community detection and subgroup discovery resulting in a description-oriented approach for.

关键词： data mining

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Formation and temporal evolution of social groups during coffee breaks 1

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5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014

作者： Atzmueller, Martin Ernst, Andreas Krebs, Friedrich Scholz, Christoph Stumme, Gerd Knowledge and Data Engineering Group Research Center for Information System Design University of Kassel Wilhelmshöher Allee 73 Kassel34121 Germany Center for Environmental Systems Research University of Kassel Wilhelmshöher Allee 47 Kassel34117 Germany Department Energy Informatics and Information Systems Fraunhofer Institute for Wind Energy and Energy System Technology Königstor 59 Kassel34119 Germany

ISBN: (数字)9783319290096

ISBN: (纸本)9783319290089

group formation and evolution are prominent topics in social contexts. This paper focuses on the analysis of group evolution events in networks of face-to-face proximity. We first analyze statistical properties of group evolution, e.g., individual activity and typical group sizes. After that, we define a set of specific group evolution events. These are analyzed in the context of an academic conference, where we provide different patterns according to phases of the conference. Specifically, we investigate group formation and evolution using real-world data collected at the LWA 2010 conference utilizing the Conferator system, and discuss patterns according to different phases of the conference. © Springer International Publishing Switzerland 2016.

关键词： Computers

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The linked data mining challenge 2015 4

The linked data mining challenge 2015

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4th Workshop on knowledge Discovery and data Mining Meets Linked Open data, Know@LOD 2015, co-located with 12th Extended Semantic Web Conference, ESWC 2015

作者： Ristoski, Petar Paulheim, Heiko Svátek, Vojtěch Zeman, Václav University of Mannheim Research Group Data and Web Science Germany University of Economics Department of Information and Knowledge Engineering Czech Republic

The 2015 edition of the Linked data Mining Challenge, conducted in conjunction with Know@LOD 2015, has been the third edition of this challenge. This year's dataset collected movie ratings, where the task was to classify well and badly rated movies. The solutions submitted reached an accuracy of almost 95%, which is a clear advancement over the baseline of 60%. However, there is still headroom for improvement, as the majority vote of the three best systems reaches an even higher accuracy. Copyright © 2015 for the individual papers by the papers' authors.

关键词： Linked data

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Ontology-supported exploratory search for physical training exercises

Ontology-supported exploratory search for physical training ...

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ISWC 2015 Posters and Demonstrations Track, ISWC-P and D 2015 - co-located with the 14th International Semantic Web Conference, ISWC 2015

作者： Kotzyba, Michael Ponomaryov, Denis Low, Thomas Thiel, Marcus Glimm, Birte Nürnberger, Andreas Data and Knowledge Engineering Group Otto von Guericke University Magdeburg Germany Institute of Artificial Intelligence University of Ulm Germany

In order to provide a qualitative support to the users during a web search, it is important to have access to a multitude of information sources simultaneously. Depending on the available domain expertise, the user can get an overview and insight to different information perspectives and compare the quality of resources. In this work, we present an exploratory search engine that simultaneously accesses internet resources and a local knowledge base given in the form of ontologies. The ontologies are used to define the search context and can be extended during exploration with new information, thus making the search process adaptive and iterative. We demonstrate our system on an example from the fitness domain, where the user searches for physical training exercises on the Web to complete a personal training plan.

关键词： Ontology

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