Context extraction from reviews for Context Aware Recommendation using Text Classification techniques

The use of machine learning algorithms in recommender systems: A systematic review

“…Secondary Study Name (Bouza & Bernstein, 2014) (Partial) user preference similarity as classification-based model similarity (Lahlou, Mountassir, Benbrahim, & Kassou, 2013) A Text Classification based method for context extraction from online reviews (Bertin-Mahieux, Eck, & Mandel, 2010) Automatic tagging of audio: The state-of-the-art (Carbone & Vlassov, 2015) Auto-Scoring of Personalised News in the Real-Time Web: Challenges, Overview and Evaluation of the State-of-the-Art Solutions (Lahlou, Benbrahimand, Mountassir, & Kassou, 2013) Context extraction from reviews for Context Aware Recommendation using Text Classification techniques (Cremonesi, Garzotto, Negro, Papadopoulos, & Turrin, 2011) Looking for "good" recommendations: A comparative evaluation of recommender systems (Bagchi, 2015) Performance and quality assessment of similarity measures in collaborative filtering using mahout (Feuerverger, He, & Khatri, 2012) Statistical significance of the netflix challenge (Shani & Gunawardana, 2013) Tutorial on application-oriented evaluation of recommendation systems (Jannach, Lerche, Gedikli, & Bonnin, 2013) What recommenders recommend -An analysis of accuracy, popularity, and sales diversity effects Table 4.11: Secondary studies shared by domain experts…”

Convolutional neural encoding of online reviews for the identification of travel group type topics on TripAdvisor

“…However, we hypothesize that differences can be extended to more specific categories such as business, family, friends, and couples, as also considered by TripAdvisor. Content-based review classifiers provide evidence that there are some content differences able to predict the trip type (Lahlou et al, 2013). Hence, we hypothesize: H2: Each trip type can be characterized by its own specific topics different than other trip types…”

CRecSys: A Context-Based Recommender System Using Collaborative Filtering and LOD

“…Hariri et al [31] proposed a contextbased music recommender system where latent topics were extracted using topic modeling techniques and used as contextual features. Similarly, Lahlou et al [32] introduced a text classification technique to infer contextual features from review documents. Table 1 presents a list of datasets used in CARS.…”