Information Retrieval (IR) Task

An Information Retrieval (IR) Task is an information search task that can extract a ranked list from a document collection given a specific IR query.

• AKA: Boolean Information Retrieval Task.
• Context:
  • input:
    • an Non-Structured Information Source, such as a text corpus or an email stream (information items that are relevant to an information goal).
    • an IR Query (often a keyword query).
    • optional: A File Format, e.g. document data or image data.
  • Task Output: an Information Retrieval Result (with one or more ranked items)
  • Task Metric:
    • an Information Retrieval Performance Metric, such as: F-score, AUC, MRR, and NDCG.
  • It can be solved by an IR System (that applies an IR algorithm).
  • It can range from being an Inexact Information Retrieval Task to being an Exact Information Retrieval Task.
  • It can range from being a Heuristic IR Task to being a Data-Driven IR Task.
  • It can range from being a Non-Domain Specific IR Task to being a Domain Specific IR Task.
  • It can range from being a Non-Personalized IR Task to being a Personalized IR Task.
  • It can support an Information Extraction Task and a Corpus Browsing Task.
  • It can be instantiated as a Information Retrieval Task Instance.
  • It can range, based on File Format, from being a Document Retrieval Task to being an Image Retrieval Task to being a ...
• Example:
  • a Web IR Task.
  • a Keyword-based Information Retrieval Task.
  • a Sentence Retrieval Task.
  • a Domain Specific IR Task such as:
    • Product Review Retrieval,
    • Literature Search,
    • News Article Retrieval,
    • Paper IR Task, ...
    • Research Publication Search Task/Research Publication Retrieval Task.
    • TREC
    • GeoCLEF Task, information retrieval based on geographical location.
  • an IR Learning-to-Rank Task.
  • …
• Counter-Example(s):
  • an Information Extraction Task, that requires the deduplicated extraction of structured.
  • a Structured Data Search Task/Structured Data Retrieval Task.
  • a Knowledge Search Task/Knowledge Retrieval Task.
• See: Keyword Search; Information Extraction, Information Retrieval Application, Full Text Search, Information Overload.

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References

2017a

• (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/information_retrieval Retrieved:2017-8-3.
  • Information retrieval (IR) is the activity of obtaining information resources relevant to an information need from a collection of information resources. Searches can be based on full-text or other content-based indexing.

    Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for metadata that describe data, and for databases of texts, images or sounds.

    Automated information retrieval systems are used to reduce what has been called “information overload”. Many universities and public libraries use IR systems to provide access to books, journals and other documents. Web search engines are the most visible IR applications.

2017b

• (Sammut & Webb, 2017) ⇒ Claude Sammut, and Geoffrey I. Webb. (2017). "Information Retrieval". In: (Sammut & Webb, 2017).
  • QUOTE: Information retrieval (IR) is a set of techniques that extract from a collection of documents those that are relevant to a given query. Initially addressing the needs of librarians and specialists, the field has evolved dramatically with the advent of the World Wide Web. It is more general than data retrieval, whose purpose is to determine which documents contain occurrences of the keywords that make up a query. Whereas the syntax and semantics of data retrieval frameworks is strictly defined, with queries expressed in a totally formalized language, words from a natural language given no or limited structure are the medium of communication for information retrieval frameworks. A crucial task for an IR system is to index the collection of documents to make their contents efficiently accessible.

2008

• (Manning et al., 2008) ⇒ Christopher D. Manning, Prabhakar Raghavan, and Hinrich Schütze. (2008). “Introduction to Information Retrieval." Cambridge University Press. ISBN:0521865719.
  • QUOTE: 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).

2008

• (Dextre Clarke et al., 2008) ⇒ Stella Dextre Clarke, Alan Gilchrist, Ron Davies and Leonard Will. (2008). “Glossary of Terms Relating to Thesauri and Other Forms of Structured Vocabulary for Information Retrieval." Willpower Information
  • QUOTE: information retrieval all the techniques and processes used to provide for identifying items relevant to an information need, from a collection or network of documents … Selection and inclusion of items in the collection are included in this definition; likewise browsing and other forms of information seeking.

1999

• (Baeza-Yates & Ribeiro-Neto 1999) ⇒ Ricardo Baeza-Yates, and Berthier Ribeiro-Neto. (1999). “Modern Information Retrieval." Addison-Wesley. ISBN:020139829X.

1992

• (Belkin & Croft, 1992) ⇒ Nicholas J. Belkin, and W. Bruce Croft. (1992). “Information Filtering and Information Retrieval: Two Sides of the Same Coin?.” In: Communications of the ACM Journal, 35(12). doi:10.1145/138859.138861
  • QUOTE: Information retrieval (IR) has been characterized in a variety of ways, ranging from a description of its goals, to relatively abstract models of its components and processes. Although not all of these characterizations have been in agreement with one another, they all tend to share some commonalities. Usually, an IR system is considered to have the function of "leading the user to those documents that will best enable him/her to satisfy his/her need for information" [17]. Somewhat more generally, "the goal of an information [retrieval] system is for the user to obtain information from the knowledge resource which helps her/him in problem management" [1]. Such functions, or goals, of IR have been described in models of the type shown in Figure 1. This model indicates basic entities and processes in the IR situation.

1983

• (Salton & McGill, 1983) ⇒ Gerard M. Salton, and Michael J. McGill. (1983). “Introduction to Modern Information Retrieval.” McGraw-Hill. ISBN:0070544840

1973

• (Farradane et al, 1973) ⇒ J. Farradane, J. M. Russell, and P. A. Yates-Mercer. (1973). “Problems in Information Retrieval: Logical jumps in the expression of information.” In: Information Storage and Retrieval, 9(2).

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