Information retrieval (IR) is the field of computer science that deals with the processing of documents containing free text, so that they can be rapidly retrieved based on keywords specified in a user’s query. The effectiveness of IR systems is measured by comparing performance on a common set of queries and documents. The meaning of the term IR can be very broad. Just getting a credit card out of your wallet so that you can type in the card number is a form of IR. However, as an academic field of study, information retrieval might be defined thus:
What is information retrieval ?
Information retrieval is generally considered as a subfield of computer science that deals with the representation, storage, and access of information. Information retrieval is concerned with the organization and retrieval of information from large database collections
Information Retrieval (IR) is the science of searching for information within relational databases, documents, text, multimedia files, and the World Wide Web. Information retrieval is accomplished by means of an information retrieval system and is performed manually or with the use of mechanization or automation. Human beings are indispensable in information retrieval. Depending on the character of the information contained in the texts output by the IR system, information retrieval can be documentary, including bibliographic, or factual. Information retrieval must be distinguished from logical information processing, without which directs replies to the questions posed by a human being are impossible. In IR, only the information that was input to the information retrieval system is sought—only that information can be found.
“Information retrieval (IR) is finding material (usually documents) of an unstructured nature (usually text) that satisfies an information need from within large collections (usually stored on computers)”.
Figure 1 show the basic block of the Information retrieval system. The field of information retrieval also covers supporting users in browsing or filtering document collections or further processing a set of retrieved documents. Given a set of documents, clustering is the task of coming up with a good grouping of the documents based on their contents. It is similar to arranging books on a bookshelf according to their topic. Given a set of topics, standing information needs, or other categories (such as suitability of texts for different age groups), classification is the task of deciding which classes, if any, each of a set of documents belongs to. It is often approached by first manually classifying some documents and then hoping to be able to classify new documents automatically.
Applications of Information retrieval
IR systems were firstly developed to help manage the huge amount of information. Many universities, corporate, and public Libraries now use Information retrieval systems to provide access to books, journals, and other documents. Information retrieval is used today in many applications. General applications of information retrieval system are as follows:
A digital library is a library in which collections are stored in digital formats and accessible by computers. The digital content may be stored locally, or accessed remotely via computer networks. A digital library is a type of information retrieval system.
Information Filtering System
An Information filtering system is a system that removes redundant or unwanted information from an information stream using (semi)automated or computerized methods prior to presentation to a human user. Its main goal is the management of the information overload and increment of the semantic signal-to-noise ratio. To do this the user’s profile is compared to some reference characteristics. These characteristics may originate from the information item (the content-based approach) or the user’s social environment (the collaborative filtering approach).
A search engine is one of the most the practical applications of IR techniques to large scale text collections. Web search engines are best‐ known examples, but many others searches exist, like: Desktop search, Enterprise search, Federated search, Mobile search, and Social search.
 Buckley, C., Voorhees, E.M., “Retrieval evaluation with incomplete information”, in Proc. ACM SIGIR, pp. 25-32, 2004
 A. Singhal, “Modern information retrieval: A brief overview,” IEEE Data Engineering Bulletin, vol. 24, no. 4, pp. 35–43, 2001
 Akram Roshdi and Akram Roohparvar, “Review: Information Retrieval Techniques and Applications”, International Journal of Computer Networks and Communications Security, Volume 3, Number 9, September 2015, pp. 373–377
 P. M. Nadkarni, “An introduction to information retrieval: applications in genomics”, Pharmacogenomics J. 2002; 2(2): pp. 96–102