[PDF] Top 20 A social trust and preference segmentation based matrix factorization recommendation algorithm
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A social trust and preference segmentation based matrix factorization recommendation algorithm
... this algorithm was divided into a memory-based collab- orative filtering algorithm and a model-based collabora- tive filtering ...filtering algorithm does not distinguish the rated item ... See full document
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A New Approach to Travel Recommendation using Dynamic Topic Model and Matrix Factorization
... the-art recommendation algorithms for ...type, recommendation type, data factors/features, problem modeling methodology, and data ...them based on the number of the involved k-partite ... See full document
8
Online Full Text
... or social, even environmental factors, the task of finding the correct description of each recipe is crucial for an effective and robust recommendation system ...efficient matrix factorization ... See full document
8
An online-updating algorithm on probabilistic matrix factorization with active learning for task recommendation in crowdsourcing systems
... task recommendation can help to provide a list of preferred tasks to work- ers in crowdsourcing ...workers’ preference on tasks and to provide an indication of worker quality on ...tasks. Based on ... See full document
29
Friend and POI recommendation based on social trust cluster in location based social networks
... Recommend based on Trust Cluster (FRTC) algorithm with the above algorithms in Foursquare and ...our algorithm FRTC has the significant advantage in recom- mendation precision and recall ... See full document
12
Exploiting Social Information in Pairwise Preference Recommender System
... because social media content and recommender systems can mu- tually benefit from one ...Many social-enhanced recommendation algorithms are proposed to improve recommendation quality of ... See full document
17
Evaluation of Accuracy between Item-Based and Matrix Factorization Recommender System
... Tapestry is one of the earliest implementations of collaborative filtering-based recommender systems. It was designed to filter e-mails received from mailing lists and newsgroup postings. In this system, each user ... See full document
9
A New Algorithm Based on Item Clustering and Matrix Factorization
... introduce social information, like relationship in Facebook, into CF recommender ...novel social CF framework that generalizes standard item-based CF to solve the cold-start ...user based on ... See full document
6
A Recommendation Technique Based on the Social Networks and Sequential Behaviors
... user’s social network can be employed to enhance the traditional recommender system, many methods have been ...a matrix factorization framework with social regularization with two ... See full document
7
Top N Recommendation with TrustSVD++ for User Trust and Item Rating with Implicit Techniques
... a trust-based lattice factorization method for ...used recommendation in item to item recommendation and User trust recommendation and an investigation of social ... See full document
5
Addressing Interpretability and Cold-Start in Matrix Factorization for Recommender Systems
... Embeddings–a matrix factorization that exploits items’ properties and past user preferences while enforcing the manifold structure exhibited by the collective ...learning algorithm based on ... See full document
7
Deep Learning based Trust Aware Recommender for Social Networks
... new recommendation technique for the trust aware recommendation in social networks based on the Deep Learning ...detection algorithm based on trust relations in ... See full document
7
A Comparative Study of Recommendation Methods for Mobile OSN Users
... internet based recommendations can’t be used for recommendation in mobile ...scoring matrix. User’s trust in the network is calculated based on the call duration, call frequency and ... See full document
7
The Application of Regional Combined Feature Variance Covariance Matrix in Point Cloud Similarity Measure
... region segmentation-based combined feature variance-covariance matrix algorithm as descriptors for point clouds ...proposed algorithm reflected regional and topological features in all ... See full document
10
Neural News Recommendation with Multi Head Self Attention
... In this paper, we propose a neural news recommendation approach with multi-head self- attention (NRMS). The core of our approach is a news encoder and a user encoder. In the news en- coder, we learn news ... See full document
6
Recommendation of Product using Hybrid Filtering Approach from Textual Reviews
... of recommendation approaches: Content based and Collaborative Filtering (CF)[2] based and Hybrid Filtering[1] based ...content based approach is to use properties of an item to predict ... See full document
9
DE Mosaicing using Matrix Factorization Iterative Tunable Method
... i.e. Matrix factorization Iterative Tunable approach, the main aim of this methodology is to improvise the reconstruction ...MFIT algorithm at each iteration this helps in avoiding the image ... See full document
8
A binary matrix factorization algorithm for protein complex prediction
... adjacent matrix of a PPI network. The proposed BYY-BMF algorithm automatically determines the cluster number while this number is pre-given for most existing BMF ...Cluster Algorithm (MCL) that ... See full document
8
Collaborative Topic Regression with Multiple Graphs Factorization for Recommendation in Social Media
... Graphs Factorization In this section, we discuss our proposed method, called CTR with multiple graphs factorization (CTR- ...latent social factor ... See full document
12
Web Page Recommender System for Effective Information Retrieval using hybridization of Trust, ACO and GA
... using trust value and is averaged based on number of users in web of trust in order to prevent the system fluctuation due to high pheromone ... See full document
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