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  2. Inverted index - Wikipedia

    en.wikipedia.org/wiki/Inverted_index

    The purpose of an inverted index is to allow fast full-text searches, at a cost of increased processing when a document is added to the database. [2] The inverted file may be the database file itself, rather than its index. It is the most popular data structure used in document retrieval systems, [3] used on a large scale for example in search ...

  3. Document retrieval - Wikipedia

    en.wikipedia.org/wiki/Document_retrieval

    Form based document retrieval addresses the exact syntactic properties of a text, comparable to substring matching in string searches. The text is generally unstructured and not necessarily in a natural language, the system could for example be used to process large sets of chemical representations in molecular biology.

  4. Vector space model - Wikipedia

    en.wikipedia.org/wiki/Vector_space_model

    Candidate documents from the corpus can be retrieved and ranked using a variety of methods. Relevance rankings of documents in a keyword search can be calculated, using the assumptions of document similarities theory, by comparing the deviation of angles between each document vector and the original query vector where the query is represented as a vector with same dimension as the vectors that ...

  5. Latent semantic analysis - Wikipedia

    en.wikipedia.org/wiki/Latent_semantic_analysis

    The original term-document matrix is presumed noisy: for example, anecdotal instances of terms are to be eliminated. From this point of view, the approximated matrix is interpreted as a de-noisified matrix (a better matrix than the original). The original term-document matrix is presumed overly sparse relative to the "true" term-document matrix.

  6. Bag-of-words model - Wikipedia

    en.wikipedia.org/wiki/Bag-of-words_model

    It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity. The bag-of-words model is commonly used in methods of document classification where, for example, the (frequency of) occurrence of each word is used as a feature for training a ...

  7. Information retrieval - Wikipedia

    en.wikipedia.org/wiki/Information_retrieval

    1983: Salton (and Michael J. McGill) published Introduction to Modern Information Retrieval (McGraw-Hill), with heavy emphasis on vector models. 1985: David Blair and Bill Maron publish: An Evaluation of Retrieval Effectiveness for a Full-Text Document-Retrieval System mid-1980s: Efforts to develop end-user versions of commercial IR systems.

  8. Search engine indexing - Wikipedia

    en.wikipedia.org/wiki/Search_engine_indexing

    Stores citations or hyperlinks between documents to support citation analysis, a subject of bibliometrics. n-gram index Stores sequences of length of data to support other types of retrieval or text mining. [13] Document-term matrix Used in latent semantic analysis, stores the occurrences of words in documents in a two-dimensional sparse matrix.

  9. Coding interview - Wikipedia

    en.wikipedia.org/wiki/Coding_interview

    Some questions involve projects that the candidate has worked on in the past. A coding interview is intended to seek out creative thinkers and those who can adapt their solutions to rapidly changing and dynamic scenarios. [citation needed] Typical questions that a candidate might be asked to answer during the second-round interview include: [7]