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English: Learning in the partial-information sequential search paradigm. The numbers display the expected values of applicants based on their relative rank (out of m total applicants seen so far) at various points in the search. Expectations are calculated based on the case when their values are uniformly distributed between 0 and 1.
In this case, the learning-to-rank problem is approximated by a classification problem — learning a binary classifier (,) that can tell which document is better in a given pair of documents. The classifier shall take two documents as its input and the goal is to minimize a loss function L ( h ; x u , x v , y u , v ) {\displaystyle L(h;x_{u},x ...
Ranking of query is one of the fundamental problems in information retrieval (IR), [1] the scientific/engineering discipline behind search engines. [2] Given a query q and a collection D of documents that match the query, the problem is to rank, that is, sort, the documents in D according to some criterion so that the "best" results appear early in the result list displayed to the user.
Otto Rank (/ r ɑː ŋ k /; Austrian German:; né Rosenfeld; 22 April 1884 – 31 October 1939) was an Austrian psychoanalyst, writer, and philosopher.Born in Vienna, he was one of Sigmund Freud's closest colleagues for 20 years, a prolific writer on psychoanalytic themes, editor of the two leading analytic journals of the era, including Internationale Zeitschrift für Psychoanalyse ...
The term was first used by Austrian psychoanalyst Otto Rank and has been popularized by developmental psychologist Gordon Neufeld. [1] In Neufeld's model, counterwill is a functional attribute of human behavior in that it protects personal boundaries and enables individuation. It has also been described as "will in reaction to the will of ...
Preference learning can be used in ranking search results according to feedback of user preference. Given a query and a set of documents, a learning model is used to find the ranking of documents corresponding to the relevance with this query. More discussions on research in this field can be found in Tie-Yan Liu's survey paper. [6]
Indexing and classification methods to assist with information retrieval have a long history dating back to the earliest libraries and collections however systematic evaluation of their effectiveness began in earnest in the 1950s with the rapid expansion in research production across military, government and education and the introduction of computerised catalogues.
The information need can be specified in the form of a search query. In the case of document retrieval, queries can be based on full-text or other content-based indexing. Information retrieval is the science [ 1 ] of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes ...