Similarity between users
Mitigating Cold Start Problem In A Personalized Recommender System
... the similarity between users, predicts an item/product and recommends to a target user which is termed as user-based collaborative ...computing similarity between ...about users, ...
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Friend matching using probabilistic topic model
... Using similarity metric, we find the interest similarity between ...G=(V,E,W)where users in the system are represented as vertices and the similarity score as edges ...is ...
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User Service Rating Prediction System by Exploring Social Users Rating Behavior
... new users these types of reviews plays a vital role in deciding whether to go for that specific service or ...social users to predict user service ratings users rating behaviours are ...represent ...
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ENERGY EFFICIENT DISTRIBUTED IMAGE COMPRESSION USING JPEG2000 IN WIRELESS SENSOR NETWORKS (WSNS)
... the similarity between users to generate recommendations, through mastering the relation between individuals to achieve ...of users which have the same or similar interests with target ...
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Typicality-Based Collaborative Filtering Recommendation System
... neighbor users, recommending simulation ...collects users‟ grading on used simulation resources as user preferences, and uses the Pearson correlation to calculate the similarity between ...
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Classifying and Filtering Users by Similarity Measures for Trust Management in Cloud Environment
... The users of different services may provide their feedbacks about the services they consumed to present their satisfaction or ...the users may provide unfair and false feedback, so it is important to detect ...
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Social Commerce Hybrid Product Recommender
... string similarity methods and decide which similarity method would be useful in increasing the accuracy of our social hybrid recommender ...relationship between top-e items (to be predicted) and the ...
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Web Service Recommendation by Predicting QoS and User's Location
... exists between users’ location closeness of and users’ QoS similarity, we propose a location-aware UPCC method to identify similar users for an active ...
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SMART CITY TRAVELLER
... This is the first and most crucial step for building a recommendation engine. The data can be collected by two means: explicitly and implicitly. Explicit data is information that is provided intentionally, i.e. input ...
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User Profiles and Identifing User Behaviour in the Cloud Computing Environment
... In this paper detection method for the illegal access to the cloud infrastructure is proposed. Detection process is based on the collaborative filtering algorithm constructed on the cloud model. Here, first of all, the ...
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Structural and Non-Structural Similarity Combination of Users in Social Networks
... Description of the train data and test data of every test series are presented in the fifth and sixth columns of the subject test (e.g. in the first test in experiment1, after dividing the available connections in the ...
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PBloofi: An Enhanced Version of BloofI in Recommender Systems
... User-based and item-based collaborative filtering methods are two of the most widely used techniques in recommender systems. While these algorithms are widely used in industry they require a considerable amount of time ...
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Wanderlust : A Personalised Travel Itinerary Recommender
... gap between optimized travel routes and user’s travel ...the similarity between user package and route package in order to recommend a personalized point of interest sequence to the ...similar ...
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Semantic Similarity Between Sentences
... semantic similarity measures in WordNet based on is-a ...the similarity we follow feature based approach which generates the similarity score in depth of word meaning level and definition level and ...
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Lexical Inference over Multi Word Predicates: A Distributional Approach
... Corpora and Preprocessing. As a reference corpus R, we use Reverb (Fader et al., 2011), a web-based corpus consisting of 15M web extrac- tions of binary relations. Each relation is a triplet of a predicate and two ...
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A NOVEL APROACH TO FEATURE BASED RECOMMENDATION SYSTEM BASED ON USER RATINGS
... of users along with the items rated by each of ...the users that strongly match with the user under consideration, thereby recommending the items that were strongly rated by the similar ...
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Using Semantic Distance to Automatically Suggest Transfer Course Equivalencies
... The SDBW module uses WordNet as a lexical knowledge base to determine the semantic close- ness between words. The path lengths and depths in the WordNet IS-A hierarchy may be used to mea- sure how strongly a word ...
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Measurement of Similarity Between Nouns
... 1965 International Conference on Computational Linguistics MEASUREMENT OF SIMILARITY BETWEEN NOUNS 10 1965 I n t e r n a t i o n a l C o n f e r e n c e on C o m p u t a t i o n a l L i n g u i s t i[.] ...
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Analyzing Entity Framework Technology for an Indoor Decoration Based Recommendation System
... similarities between users [4], ...the users by using the collaborative filtering ...[6]. Similarity calculation methods, which is an important step of the collaborative filtering methods, ...
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Soft Computing Based Recommendation System: A Comparative Study
... In the very first stage, related data is collected to provide its users a quality recommendation. The user profile has to be constructed very well for the recommendation agent. The system has to be fed as much as ...
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