In probability model the similarity between a query and a document is governed by various statistical and probabilistic laws, for example, Bayesian inference rules. The nature of TR tasks implies multitude of possibilities of various approaches from different disciplines. Linguistics and Formal Languages provide rich knowledge on parsing and interpreting the text, while techniques from artificial intelligence, machine learning, knowledge representation and pattern recognition shed light on how to model the content of the text and search on the representations effectively. The availability of large text collections also enables the statistics approaches, which have already been proved robust even with only modest linguistics knowledge. Early effort of image retrieval was based on text such as file names, keywords, etc.
Indexing mainly deals with the indexing structure, similarity distance and clustering.
User interface, relevance feedback, result merging, etc.