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 Pasquale Lops

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Average citations per article3.84
Citation Count288
Publication count75
Publication years1997-2017
Available for download23
Average downloads per article321.43
Downloads (cumulative)7,393
Downloads (12 Months)1,562
Downloads (6 Weeks)201
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75 results found Export Results: bibtexendnoteacmrefcsv

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1
November 2017 Knowledge-Based Systems: Volume 136 Issue C, November 2017
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 0

The recent spread of Linked Open Data (LOD) fueled the research in the area of Recommender Systems, since the (semantic) data points available in the LOD cloud can be exploited to improve the performance of recommendation algorithms by enriching item representations with new and relevant features.In this article we investigate ...
Keywords: Classifiers, Machine learning, Semantics, Linked Open Data, Recommender Systems

2
November 2017 Pattern Recognition Letters: Volume 99 Issue C, November 2017
Publisher: Elsevier Science Inc.
Bibliometrics:
Citation Count: 0

A multimodal framework for monitoring users attitude and profile.A dynamic model for monitoring user liking attitude.We integrated the module in a content-based recommender system. Conversational recommender systems produce personalized recommendations of potentially useful items by utilizing natural language dialogues for detecting user preferences, as well as for providing recommendations. In ...
Keywords: 41A05, Behavioral analysis, 41A10, 65D17, Social robots, 65D05, Conversational recommender systems, User profiling

3 published by ACM
August 2017 RecSys '17: Proceedings of the Eleventh ACM Conference on Recommender Systems
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 53,   Downloads (12 Months): 241,   Downloads (Overall): 241

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In this paper we propose a multi-criteria recommender system based on collaborative filtering (CF) techniques, which exploits the information conveyed by users' reviews to provide a multi-faceted representation of users' interests. To this end, we exploited a framework for opinion mining and sentiment analysis , which automatically extracts relevant aspects ...
Keywords: opinion mining, recommender systems, sentiment analysis

4 published by ACM
August 2017 ACM SIGIR Forum: Volume 51 Issue 1, June 2017
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 13,   Downloads (12 Months): 28,   Downloads (Overall): 28

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This article reports on the CBRecSys 2016 workshop, the third edition of the workshop on New Trends in Content-based Recommender Systems , co-located with RecSys 2016 in Boston, MA. Content-based recommendation has been applied successfully in many different domains, but it has not seen the same level of attention as ...

5 published by ACM
July 2017 UMAP '17: Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 40,   Downloads (12 Months): 322,   Downloads (Overall): 322

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In this paper we investigate the effectiveness of Recurrent Neural Networks (RNNs) in a top-N content-based recommendation scenario. Specifically, we propose a deep architecture which adopts Long Short Term Memory (LSTM) networks to jointly learn two embeddings representing the items to be recommended as well as the preferences of the ...
Keywords: neural networks, recommender systems

6 published by ACM
July 2017 UMAP '17: Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 7,   Downloads (12 Months): 55,   Downloads (Overall): 55

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In this article we propose a hybrid recommendation framework based on classification algorithms as Random Forests and Naive Bayes. We fed the framework with several heterogeneous groups of features, and we investigate to what extent features gathered from the Linked Open Data (LOD) cloud (as the genre of a movie ...
Keywords: supervised learning, linked data, recommender systems

7
March 2017 Information Processing and Management: an International Journal: Volume 53 Issue 2, March 2017
Publisher: Pergamon Press, Inc.
Bibliometrics:
Citation Count: 0

We investigate the impact of the integration of the knowledge coming from the LOD cloud in a graph-based recommendation framework.We propose a methodology to automatically feed a graph-based recommendation algorithm with features coming from the LOD cloud.We give guidelines to drive the choice of the feature selection technique, according to ...
Keywords: Diversity, Recommender systems, Graphs, Linked open data, PageRank, Feature selection

8
December 2016 Information Sciences: an International Journal: Volume 374 Issue C, December 2016
Publisher: Elsevier Science Inc.
Bibliometrics:
Citation Count: 0

The growth of the Web is the most influential factor that contributes to the increasing importance of text retrieval and filtering systems. On one hand, the Web is becoming more and more multilingual, and on the other hand users themselves are becoming increasingly polyglot. In this context, platforms for intelligent ...
Keywords: Concept-based representations, Content-based recommender systems, BabelNet, Wikipedia

9 published by ACM
September 2016 RecSys '16: Proceedings of the 10th ACM Conference on Recommender Systems
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 4,   Downloads (12 Months): 62,   Downloads (Overall): 135

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While content-based recommendation has been applied successfully in many different domains, it has not seen the same level of attention as collaborative filtering techniques have. However, there are many recommendation domains and applications where content and metadata play a key role, either in addition to or instead of ratings and ...
Keywords: context, semantics, text reviews, user-generated content, content-based recommendation, implicit feedback, recommender systems

10 published by ACM
September 2016 RecSys '16: Proceedings of the 10th ACM Conference on Recommender Systems
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 5,   Downloads (12 Months): 64,   Downloads (Overall): 131

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This paper presents T-RecS (Temporal analysis of Recommender Systems conference proceedings), a framework that supplies services to analyze the Recommender Systems Conference proceedings from the first edition, held in 2007, to the last one, held in 2015, under a temporal point of view. The idea behind T-RecS is to identify ...
Keywords: temporal random indexing, explicit semantic analysis, natural language processing, distributional semantics

11 published by ACM
September 2016 RecSys '16: Proceedings of the 10th ACM Conference on Recommender Systems
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 17,   Downloads (12 Months): 165,   Downloads (Overall): 332

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In this paper we present ExpLOD, a framework which exploits the information available in the Linked Open Data (LOD) cloud to generate a natural language explanation of the suggestions produced by a recommendation algorithm. The methodology is based on building a graph in which the items liked by a user ...
Keywords: linked open data cloud, user modeling, explanation, recommender systems

12 published by ACM
July 2016 UMAP '16: Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization
Publisher: ACM
Bibliometrics:
Citation Count: 7
Downloads (6 Weeks): 12,   Downloads (12 Months): 120,   Downloads (Overall): 187

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The ever increasing interest in semantic technologies and the availability of several open knowledge sources have fueled recent progress in the field of recommender systems. In this paper we feed recommender systems with features coming from the Linked Open Data (LOD) cloud - a huge amount of machine-readable knowledge encoded ...
Keywords: pagerank, feature selection, diversity, graph-based recommender systems, graphs, linked open data

13 published by ACM
July 2016 UMAP '16: Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 3,   Downloads (12 Months): 36,   Downloads (Overall): 61

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This paper presents the results of The Italian Hate Map, a research project aiming to monitor the level of intolerance of the Italian country by mining the content posted on social networks. Within the project, a pipeline of algorithms for data extraction, semantic processing, sentiment analysis and content classification has ...
Keywords: community behavior, sentiment analysis, urban informatics, content processing, semantics, social media

14
December 2015 Information Systems: Volume 54 Issue C, December 2015
Publisher: Elsevier Science Ltd.
Bibliometrics:
Citation Count: 1

The recent huge availability of data coming from mobile phones, social networks and urban sensors leads research scientists to new opportunities and challenges. For example, mining micro-blogs content to unveil latent information about people sentiment and opinions is drawing more and more attention, since it can improve the understanding of ...
Keywords: Semantics, Sentiment analysis, Social networks, Text analytics, Smart cities

15 published by ACM
September 2015 EMPIRE '15: Proceedings of the 3rd Workshop on Emotions and Personality in Personalized Systems 2015
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 3,   Downloads (12 Months): 49,   Downloads (Overall): 160

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Emotions play a crucial role in the decision making process. Frequently, choices are strongly influenced by the mood of the moment, and the same person could take different decisions at different time on the same topic. Recommender systems, that are definitively recognized as tools for supporting the decision making process, ...
Keywords: Content-based Recommender System, Sentiment Analysis, Emotion-aware Recommender System

16 published by ACM
September 2015 EMPIRE '15: Proceedings of the 3rd Workshop on Emotions and Personality in Personalized Systems 2015
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 0,   Downloads (12 Months): 33,   Downloads (Overall): 119

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A conversational recommender system should interactively assist users in order to understand their needs and preferences and produce personalized recommendations accordingly. While traditional recommender systems use a single-shot approach, the conversational ones refine their suggestions during the conversation since they gain more knowledge about the user. This approach can be ...
Keywords: Conversational Recommender Systems, Behavioral Analysis

17
September 2015 Decision Support Systems: Volume 77 Issue C, September 2015
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 0

Recommendation of financial investment strategies is a complex and knowledge-intensive task. Typically, financial advisors have to discuss at length with their wealthy clients and have to sift through several investment proposals before finding one able to completely meet investors' needs and constraints. As a consequence, a recent trend in wealth ...
Keywords: Case-based reasoning, Finance, Diversity, Investment portfolios, Personalization, Recommender systems

18
September 2015 Information Processing and Management: an International Journal: Volume 51 Issue 5, September 2015
Publisher: Pergamon Press, Inc.
Bibliometrics:
Citation Count: 6

We design a Knowledge Infusion (KI) process for providing systems with background knowledge.We design a KI-based recommendation algorithm for providing serendipitous recommendations.An in vitro evaluation shows the effectiveness of the proposed approach.We collected implicit emotional feedback on serendipitous recommendations.Results show that serendipity is moderately correlated with surprise and happiness. Recommender ...
Keywords: Knowledge representation, Spreading activation, Affective feedback, Facial expressions, Serendipity problem, Recommender systems

19 published by ACM
May 2015 WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 4,   Downloads (12 Months): 39,   Downloads (Overall): 149

Full text available: PDFPDF
In this work we present a semantic recommender system able to suggest doctors and hospitals that best fit a specific patient profile. The recommender system is the core component of the social network named HealthNet (HN). The recommendation algorithm first computes similarities among patients, and then generates a ranked list ...
Keywords: smart health, social network, recommender system, e-health

20 published by ACM
May 2015 WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 4,   Downloads (12 Months): 20,   Downloads (Overall): 122

Full text available: PDFPDF
This paper presents a domain-agnostic framework for intelligent processing of textual streams coming from social networks. The framework implements a pipeline of techniques for semantic representation, sentiment analysis, automatic content classification, and provides an analytics console to get some findings from the extracted data. The effectiveness of the platform has ...
Keywords: natural language processing, semantic, sentiment analysis, smart cities, big data, entity linking



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