Service component recommendation based on LSTM

Hashtag Recommendation with Topical Attention-Based LSTM

Microblogging services allow users to create hashtags to categorize their posts. In recent years, the task of recommending hashtags for microblogs has been given increasing attention. However, most of existing methods depend on hand-crafted features. Motivated by the successful use of long short-term memory (LSTM) for many natural language processing tasks, in this paper, we adopt LSTM to learn...

QoS-based Web Service Recommendation using Popular-dependent Collaborative Filtering

Since, most of the organizations present their services electronically, the number of functionally-equivalent web services is increasing as well as the number of users that employ those web services. Consequently, plenty of information is generated by the users and the web services that lead to the users be in trouble in finding their appropriate web services. Therefore, it is required to provi...

SaaS Service Recommendation System Based on

The emergence of Grid computing and Service Oriented Architectures has led to evolution in terms of how applications are built and managed. Software as a service (SaaS), also known as the on-demand model, is changing the way businesses of all sizes and in all industries use software. These services are provided by different vendors. Some time similar services are provided by the various vendors...

Composite Service Recommendation Based on Bayes Theorem

An LSTM-Based Dynamic Customer Model for Fashion Recommendation

Online fashion sales present a challenging use case for personalized recommendation: Stores offer a huge variety of items in multiple sizes. Small stocks, high return rates, seasonality, and changing trends cause continuous turnover of articles for sale on all time scales. Customers tend to shop rarely, but often buy multiple items at once. We report on backtest experiments with sales data of 1...