Blar i NTNU Open på forfatter "Zhang, Lemei"
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Dynamic attention-based explainable recommendation with textual and visual fusion
Liu, Peng; Zhang, Lemei; Gulla, Jon Atle (Journal article; Peer reviewed, 2019)Explainable recommendation, which provides explanations about why an item is recommended, has attracted growing attention in both research and industry communities. However, most existing explainable recommendation methods ... -
Dynamic attention-integrated neural network for session-based news recommendation
Zhang, Lemei; Liu, Peng; Gulla, Jon Atle (Journal article; Peer reviewed, 2019)Online news recommendation aims to continuously select a pool of candidate articles that meet the temporal dynamics of user preferences. Most of the existing methods assume that all user-item interaction history are equally ... -
An Educational News Dataset for Recommender Systems
Xing, Yujie; Mohallick, Itishree; Gulla, Jon Atle; Özgöbek, Özlem; Zhang, Lemei (Journal article; Peer reviewed, 2021)Datasets are an integral part of contemporary research on recommender systems. However, few datasets are available for conventional recommender systems and even very limited datasets are available when it comes to ... -
Exploring Multifaced User Modelling in Textual Data Streams
Zhang, Lemei (Doctoral theses at NTNU;2021:380, Doctoral thesis, 2021)User modelling technologies play an important role in the success of many online applications such as recommender systems. However, it is far from enough to solve the cold-start issue and data sparsity problem commonly ... -
Learning multi-granularity dynamic network representations for social recommendation
Liu, Peng; Zhang, Lemei; Gulla, Jon Atle (Journal article; Peer reviewed, 2019)With the rapid proliferation of online social networks, personalized social recommendation has become an important means to help people discover useful information over time. However, the cold-start issue and the special ... -
Multilingual Review-aware Deep Recommender System via Aspect-based Sentiment Analysis
Liu, Peng; Zhang, Lemei; Gulla, Jon Atle (Peer reviewed; Journal article, 2021)With the dramatic expansion of international markets, consumers write reviews in different languages, which poses a new challenge for Recommender Systems (RSs) dealing with this increasing amount of multilingual information. ... -
Real-time social recommendation based on graph embedding and temporal context
Liu, Peng; Zhang, Lemei; Gulla, Jon Atle (Journal article; Peer reviewed, 2018)With the rapid proliferation of online social networks, personalized social recommendation has become an important means to help people discover their potential friends or interested items in real-time. However, the ... -
Recommending on graphs: a comprehensive review from a data perspective
Zhang, Lemei; Liu, Peng; Gulla, Jon Atle (Peer reviewed; Journal article, 2023)Recent advances in graph-based learning approaches have demonstrated their effectiveness in modelling users’ preferences and items’ characteristics for Recommender Systems (RSs). Most of the data in RSs can be organized ... -
Semantic User Behaviour Prediction in Online News - Applying Topic Modeling, Community Detection, and User Modeling for News Recommendation
Kjekstad, Nina; Reknes, Elida Karina (Master thesis, 2018)In recent years, predicting user behaviour has become increasingly important within the news recommendation area. Knowledge of behavioural patterns offers valuable insight for developing efficient and user friendly services, ...