RECSYS 2015 - PDF Preprint Papers

RECSYS 2015 ACM Conference On Recommender Systems

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RECSYS
2015
ACM

61views Control Systems» more RECSYS 2015»

Word Embedding Techniques for Content-based Recommender Systems: An Empirical Evaluation

8 years 7 months ago

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This work presents an empirical comparison among three widespread word embedding techniques as Latent Semantic Indexing, Random Indexing and the more recent Word2Vec. Speciﬁcall...

Cataldo Musto, Giovanni Semeraro, Marco de Gemmis,...

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Id	Views	Title	Status

1	61	Word Embedding Techniques for Content-based Recommender Systems: An Empirical Evaluation	claim
2	48	News2Images: Automatically Summarizing News Articles into Image-Based Contents via Deep Learning	claim
3	39	"Where Far Can Be Close": Finding Distant Neighbors In Recommender Systems	claim
4	37	Context-Aware Event Recommendation in Event-based Social Networks	claim
5	35	Beyond "Hitting the Hits": Generating Coherent Music Playlist Continuations with the Right Tracks	claim
6	31	Predicting Personality Traits with Instagram Pictures	claim
7	30	A Probabilistic Model for Using Social Networks in Personalized Item Recommendation	claim
8	29	Adaptation and Evaluation of Recommendations for Short-term Shopping Goals	claim
9	28	Preference-oriented Social Networks: Group Recommendation and Inference	claim
10	28	Parsimonious and Adaptive Contextual Information Acquisition in Recommender Systems	claim
11	27	Merging Latent Factors and Tags to Increase Interactive Control of Recommendations	claim
12	25	Item Familiarity Effects in User-Centric Evaluations of Recommender Systems	claim
13	25	The Continuous Cold-start Problem in e-Commerce Recommender Systems	claim
14	24	Overlapping Community Regularization for Rating Prediction in Social Recommender Systems	claim
15	24	Exploring Statistical Language Models for Recommender Systems	claim
16	24	Risk-Hedged Venture Capital Investment Recommendation	claim
17	23	Extended Recommendation Framework: Generating the Text of a User Review as a Personalized Summary	claim
18	23	Explaining Contextual Recommendations: Interaction Design Study and Prototype Implementation	claim
19	23	Context-Aware Recommendations for Mobile Shopping	claim
20	23	Asymmetric Recommendations: The Interacting Effects of Social Ratings? Direction and Strength on Users' Ratings	claim
21	22	Automatic Selection of Linked Open Data Features in Graph-based Recommender Systems	claim
22	22	Interaction Design in a Mobile Food Recommender System	claim
23	21	Towards Improving Top-N Recommendation by Generalization of SLIM	claim
24	21	Letting Users Choose Recommender Algorithms: An Experimental Study	claim
25	21	Style Recommendation for Fashion Items using Heterogeneous Information Network	claim
26	21	Analysis of User-generated Content for Improving YouTube Video Recommendation	claim
27	21	Cross-Document Search Engine For Book Recommendation	claim
28	21	Conceptual Impact-Based Recommender System for CiteSeerx	claim
29	20	Are Real-World Place Recommender Algorithms Useful in Virtual World Environments?	claim
30	20	Exploiting Reviews to Guide Users' Selections	claim
31	20	HyPER: A Flexible and Extensible Probabilistic Framework for Hybrid Recommender Systems	claim
32	19	Generic knowledge-based Analysis of Social Media for Recommendations	claim
33	19	Automatic Recommendations of Categories for Geospatial Entities	claim
34	19	30Music Listening and Playlists Dataset	claim
35	19	Top-N Recommendation with Missing Implicit Feedback	claim
36	19	Automated Recommendation of Healthy, Personalised Meal Plans	claim
37	18	Replicable Evaluation of Recommender Systems	claim
38	18	The Recommendation Game: Using a Game-with-a-Purpose to Generate Recommendation Data	claim
39	18	Network-Based Extension of Multi-Relational Factorization Models	claim
40	18	Listener-Inspired Automated Music Playlist Generation	claim
41	17	Putting Users in Control of their Recommendations	claim
42	17	ExcUseMe: Asking Users to Help in Item Cold-Start Recommendations	claim
43	17	Exploiting Geo-Spatial Preference for Personalized Expert Recommendation	claim
44	17	Exploiting Regression Trees as User Models for Intent-Aware Multi-attribute Diversity	claim
45	16	Location-Aware Recommendation Systems: Where We Are and Where We Recommend to Go	claim
46	16	Personalized Location Recommendation by Aggregating Multiple Recommenders in Diversity	claim
47	16	Probability-based Approach for Predicting E-commerce Consumer Behaviour Using Sparse Session Data	claim
48	16	From Sensors to Songs: A Learning-Free Novel Music Recommendation System using Contextual Sensor Data	claim
49	16	Inspection Mechanisms for Community-based Content Discovery in Microblogs	claim
50	15	Image Discovery and Insertion for Custom Publishing	claim
51	15	Personality-Based Recommendations: Evidence from Amazon.com	claim
52	15	Recommendation with the Right Slice: Speeding Up Collaborative Filtering with Factorization Machines	claim
53	15	3rd International Workshop on News Recommendation and Analytics (INRA 2015)	claim
54	14	Two-Stage Approach to Item Recommendation from User Sessions	claim
55	14	Measuring the Concentration Reinforcement Bias of Recommender Systems	claim
56	14	Recommender Systems for the People - Enhancing Personalization in Web Augmentation	claim
57	14	Recommending Fair Payments for Large-Scale Social Ridesharing	claim
58	13	Good Times Bad Times: A Study on Recency Effects in Collaborative Filtering for Social Tagging	claim
59	13	Online Recommender Systems based on Data Stream Management Systems	claim
60	13	An Adaptive Electronic Menu System for Restaurants	claim
61	13	Predicting Online Performance of News Recommender Systems Through Richer Evaluation Metrics	claim
62	13	Do You Have a Pop Face? Here is a Pop Song. Using Profile Pictures to Mitigate the Cold-start Problem in Music Recommender Systems	claim
63	12	Fostering Knowledge Exchange Using Group Recommendations	claim
64	12	Recommender Systems for Product Bundling	claim
65	12	A Personalised Reader for Crowd Curated Content	claim
66	12	LocalRec'15: Workshop on Location-Aware Recommendations	claim
67	12	How to Interpret Implicit User Feedback?	claim
68	11	Recommendations to Enhance Children Web Searches	claim
69	10	Analysing Compression Techniques for In-Memory Collaborative Filtering	claim
70	10	A Recommendation-Based Book-Exchange System Without Using Wish Lists	claim
71	9	Next Basket Recommendation with Neural Networks	claim
72	9	Towards Automatic Meal Plan Recommendations for Balanced Nutrition	claim
73	9	FutureView: Enhancing Exploratory Image Search	claim
74	6	Tackling Cold-Start Users in Recommender Systems with Indoor Positioning Systems	claim

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