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Everything about Implicit data collection
Implicit data collection refers to techniques in human–computer interaction and recommender systems that infer user preferences from observed behavior rather than explicit input. Wikipedia →
🧠Start here: a 6-step reading path
- Read the overview: Implicit data collectionA 5-minute orientation
- Pick up a classic book: The C Programming LanguageThe most-reprinted book on the subject
- Read the landmark paper: Automated Collection of Data on a Person: Implicit Principles of Legal RegulationCited 1 times
- Go sideways: Cold start (recommender systems)A closely related topic
- Go sideways: Collaborative filteringA closely related topic
đź“– Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
đź“š Books worth reading
The C Programming LanguageBrian W. Kernighan, Dennis MacAlistair Ritchie · 1978
Objects first with JavaDavid J. Barnes, Michael Kolling · 2002
Cartesian meditationsEdmund Husserl, Dorion Cairns · 1960
The Authoritarian DynamicKaren Stenner · 2001
Introduction to Computing Using PythonLjubomir Perkovic · 2011
Engineering Modelling and AnalysisDavid Walker, Michael Leonard · 2009
Open GovernmentDaniel Lathrop · 2010
Pervasive Computing and the Networked WorldQiaohong Zu · 2013
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
đź”— Related topics
- Cold start (recommender systems) Cold start is a potential problem in computer-based information systems which involves a degree of automated data modelling. Specifically, it concerns…
- Collaborative filtering Collaborative filtering (CF) is, besides content-based filtering, one of two major techniques used by recommender systems. Collaborative filtering has…
- Recommender system A recommender system, also called a recommendation engine or content discovery platform is a type of information filtering system that aims to suggest…
- Matrix factorization (recommender systems) Matrix factorization is a class of collaborative filtering algorithms used in recommender systems. Matrix factorization algorithms work by decomposing…
- Knowledge-based recommender system Knowledge-based recommender systems (knowledge based recommenders) are a specific type of recommender system that are based on explicit knowledge about…
- Algorithmic curation Algorithm curation is the selection of online media by technologies such as recommender systems and personalized search. Curation entails the selective…
- Active learning (machine learning) Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source)…
- GroupLens Research 44°58′27″N 93°13′57″W / 44.974280°N 93.232502°W / 44.974280; -93.232502 GroupLens Research is a human–computer interaction research lab in the Department…