Recommendation, Information Retrieval, and Exploratory Search

Dear Colleagues,

Recommendation, information retrieval, and exploratory search are prominent, interrelated tasks in intelligent information access.

Recommender systems perform information filtering and predict ratings or preferences of users among different content items, based on incomplete information on content features and user preferences, with multiple approaches such as collaborative and content-based filtering approaches and reinforcement learning approaches. Information retrieval, in turn, aims at retrieving and ranking content based on its relevance to a user's information need, often expressed by a query and its refinements through filtering and relevance feedback, ranging from general web search to product search and other domain-specific search settings. Lastly, exploratory search can be seen as an information retrieval setting where the user must not only retrieve relevant results but also become familiar with a body of knowledge to complete more complex tasks, so that the specific search intent may evolve as the task goes on.

For each of these general tasks, several models of content, including language models for text and content models of other data types, models of user intent, scoring methods, interaction paradigms and interfaces, and evaluation methodologies, have been designed. These are based on a variety of statistical and machine learning approaches, as well as several approaches from information visualization, visual analytics and human–technology interaction for interactive systems. In this Special Issue, we are seeking articles that represent the state of the art and novel approaches in these different tasks. We are especially interested in articles in the intersection of these tasks: targeting a combination of their settings and learning goals, or bridging methodological approaches across the tasks.

Prof. Dr. Jaakko Peltonen
Guest Editor

Manuscript Submission Information

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• information retrieval
• recommendation system
• exploratory search
• intelligent information access
• machine learning
• visual analytics