FM-based: Algorithm research on rural tourism recommendation combining seasonal and distribution features.

• This is the first time that recommended technology has been applied to rural tourism. • Proposed the FM recommendation algorithm combining the seasonal and distribution features. • Proposed the extraction, transformation and application method of the seasonal feature. • Proposed the extraction, transformation and application method of the geographical distribution feature. Recommended technologies for the tourism system, such as the travelocity.com and visiteurope.com, have gained tremendous popularity in the past few years. Although many research works have been dedicated to improving recommendation services and overcoming recommendation challenges, little attention has been attached to the application of recommended technology in Rural Tourism. In order to solve the difficult 'what to choose' problem caused by information overload, this paper combines the features of Rural Tourism, giving a first attempt in this field. First, an effective method of seasonal feature extraction is proposed. Next, a detailed method of geographical distribution feature extraction is described. In particular, a block-number basing on the geographical distribution feature to the Attractions is proposed. Furthermore, the FM-based (Factorization Machines) algorithm is presented as a recommended solution for Rural Tourism. Finally, the comparative experiments are provided to prove the effectiveness of this solution. [ABSTRACT FROM AUTHOR]