Information Retrieval (IR) Task

An Information Retrieval (IR) Task is an information processing task that involves locating, extracting, and organizing relevant information retrieval items from an information retrieval resource in response to an information retrieval need.

• Context:
  • It can typically accept information retrieval query input to define the information retrieval scope.
  • It can typically process non-structured information sources such as text corpuses or email streams containing information retrieval items relevant to an information retrieval goal.
  • It can typically utilize keyword querys to express information retrieval needs.
  • It can typically produce information retrieval results containing one or more information retrieval ranked items.
  • It can typically be evaluated using information retrieval performance metrics such as information retrieval F-score, information retrieval AUC, information retrieval MRR, and information retrieval NDCG.
  • ...
  • It can often interpret natural language querys to determine information retrieval intent.
  • It can often incorporate user feedback to refine information retrieval results.
  • It can often handle multimodal content including text, images, audio, and video.
  • It can often implement relevance ranking algorithms to prioritize information retrieval results.
  • ...
  • It can range from being an Inexact Information Retrieval Task to being an Exact Information Retrieval Task, depending on its information retrieval matching precision.
  • It can range from being a Heuristic Information Retrieval Task to being a Data-Driven Information Retrieval Task, depending on its information retrieval algorithmic approach.
  • It can range from being a Non-Domain Specific Information Retrieval Task to being a Domain Specific Information Retrieval Task, depending on its information retrieval domain specialization.
  • It can range from being a Non-Personalized Information Retrieval Task to being a Personalized Information Retrieval Task, depending on its information retrieval user adaptation.
  • It can range from being a Document Information Retrieval Task to being an Image Information Retrieval Task, depending on its information retrieval content type.
  • It can range from being a Human-Performed Information Retrieval Task to being an Automated Information Retrieval Task, depending on its information retrieval execution method.
  • ...
  • It can support an Information Extraction Task by providing relevant documents for information extraction processing.
  • It can facilitate a Corpus Browsing Task through information retrieval navigation structures.
  • It can be instantiated as an Information Retrieval Task Instance with specific parameters.
  • It can be supported by an Information Retrieval System that applies an information retrieval algorithm.
  • ...
• Examples:
  • Information Retrieval Task Types, such as:
    • General-Purpose Information Retrieval Tasks, such as:
      • Web Information Retrieval Task for internet content discovery.
      • Keyword-based Information Retrieval Task for term-focused information finding.
      • Sentence Information Retrieval Task for precise text segment location.
    • Domain-Specific Information Retrieval Tasks, such as:
      • Product Review Information Retrieval Task for consumer opinion discovery.
      • Literature Information Retrieval Task for scholarly content identification.
      • News Article Information Retrieval Task for current event information access.
      • Research Publication Information Retrieval Task for academic knowledge discovery.
    • Specialized Information Retrieval Tasks, such as:
      • TREC Information Retrieval Task for standardized retrieval evaluation.
      • GeoCLEF Information Retrieval Task for geographical location-based information retrieval.
      • Information Retrieval Learning-to-Rank Task for optimization of result ranking.
  • ...
• Counter-Examples:
  • An Information Extraction Task, which focuses on structured information identification from unstructured text rather than document retrieval.
  • A Structured Data Retrieval Task, which operates on database content with predefined schema rather than unstructured information sources.
  • A Knowledge Retrieval Task, which focuses on fact retrieval from knowledge bases rather than document collections.
  • A Document Classification Task, which assigns category labels to documents rather than retrieving relevant documents.
  • A Text Generation Task, which creates new content rather than locating existing information.
• See: Keyword Search, Information Extraction, Information Retrieval System, Information Retrieval Algorithm, Full Text Search, Information Overload, Information Retrieval Model.

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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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