Information filtering and information retrieval: two sides of the same coin?

By Nicholas J. Belkin, W. Bruce Croft. 1992

Subfields: Information Retrieval & Search, Recommender Systems

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Citations in the corpus

Machine learning in automated text categorization (2001, neutral): “Text filtering is the activity of classifying a stream of incoming documents dispatched in an asynchronous way by an information producer to an information consumer [Belkin and Croft 1992].”
We know what @you #tag: does the dual role affect hashtag adoption? (2012, methodology): “It is worth mentioning that while the relevance measure reflects the intuition behind many content filtering services [2], the preference measures reflect the intuition behind a common approach to collaborative filtering - to first establish the similarity among items, and then recommend items that ”
Personalized Search (2015, methodology): “Information Retrieval (IR) is the activity of obtaining information resources relevant to an information need from a collection of information resources [1].”
Hybrid Systems for Personalized Recommendations (2003, methodology): “Content-based recommendation is an outgrowth and continuation of information filtering research and is based on the idea of recommendation as classification [ 3 ].”
Hybrid Recommender Systems: Survey and Experiments (2002, background): “…known as the ’early rater’ problem, since the ﬁrst person to rate an item gets little beneﬁt from doing so: such early ratings do not improve a user’s ability to match against others (This makes it necessary for recommender systems to provide other incentives to encourage users to provide ratings.”
Content-Based Recommendation Systems (2007, methodology): “Belkin & Croft [5] surveyed some of the first content-based recommendation systems and noted that they made use of technology related to information retrieval such as tf*idf and Rocchio’s method.”
Integration of news content into web results (2009, background): “In information ltering, given a query or seed document, the system must decide which documents to present the user [ 5 ].”
Ontology-Based Integration of Information - A Survey of Existing Approaches (2001, background): “Finding suitable information sources is a problem addressed in the areas of information retrieval and information filtering [Belkin and Croft, 1992].”
Understanding and improving automated collaborative filtering systems (2000, background): “Information filtering deals with continuous information streams while information retrieval deals with mostly static data stores [9].”
Query Expansion Techniques for Information Retrieval: a Survey (2017, unknown): “Reference [28] discusses the relationship between IR and IF and establishes that IF is a special kind of IR, and has the same research challenges/outcomes.”
BizTalk Server 2000 Business Process Orchestration. (2001, unknown): “The field has developed techniques to attack many different problems like information filtering [2], topic detection and tracking (or TDT) [1], speech retrieval [13], cross-language retrieval [9], question answering [19], and many more.”
Scrutinizing an algorithmic technique: the Bayes classifier as interested reading of reality (2017, background): “Bayes classi-ﬁ ers are also often referred to as Bayesian ﬁ lters , pointing to the observation that tasks like search, classi ﬁ cation, and ﬁ ltering are closely related from a technical perspective (cf., Belkin & Croft, 1992).”