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Search and recommendation are the two most common approaches used by peopleto obtain information. They share the same goal -- satisfying the user'sinformation need at the right time. There are already a lot of Internetplatforms and Apps providing both search and recommendation services, showingus the demand and opportunity to simultaneously handle both tasks. However,most platforms consider these two tasks independently -- they tend to trainseparate search model and recommendation model, without exploiting therelatedness and dependency between them. In this paper, we argue that jointlymodeling these two tasks will benefit both of them and finally improve overalluser satisfaction. We investigate the interactions between these two tasks inthe specific information content service domain. We propose first integratingthe user's behaviors in search and recommendation into a heterogeneous behaviorsequence, then utilizing a joint model for handling both tasks based on theunified sequence. More specifically, we design the Unified Information Searchand Recommendation model (USER), which mines user interests from the integratedsequence and accomplish the two tasks in a unified way.

USER: A Unified Information Search and Recommendation Model based on Integrated Behavior Sequence