Link mining

Abstract

Many datasets of interest today are best described as a linked collection of interrelated objects. These may represent homogeneous networks, in which there is a single-object type and link type, or richer, heterogeneous networks, in which there may be multiple object and link types (and possibly other semantic information). Examples of homogeneous networks include single mode social networks, such as people connected by friendship links, or the WWW, a collection of linked web pages. Examples of heterogeneous networks include those in medical domains describing patients, diseases, treatments and contacts, or in bibliographic domains describing publications, authors, and venues. Link mining refers to data mining techniques that explicitly consider these links when building predictive or descriptive models of the linked data. Commonly addressed link mining tasks include object ranking, group detection, collective classification, link prediction and subgraph discovery. While network analysis has been studied in depth in particular areas such as social network analysis, hypertext mining, and web analysis, only recently has there been a cross-fertilization of ideas among these different communities. This is an exciting, rapidly expanding area. In this article, we review some of the common emerging themes.

Link prediction in complex networks: A survey

“…An important scientific issue relevant to network analysis is the so-called information retrieval [6,7], which aims at finding material of an unstructured nature that satisfies an information need from large collections [8]. It can also be viewed as prediction of relations between words and documents and is now further extended to stand for a number of problems on link mining, wherein link prediction is the most fundamental problem that attempts to estimate the likelihood of the existence of a link between two nodes, based on observed links and the attributes of nodes [9].…”

Analyzing and Detracting Negative Emotion Contagion Influence in Online Social Networks - Position Paper

“…Link mining is an emerging research area and a data-mining technique that takes into account the links between objects and entities while building predictive or descriptive models [12]- [15]. A popular task in link mining is link-based classification, which predicts an object's category based not only on its attributes but also the links it participates in and on attributes of objects linked by some path of edges [12], [16].…”

“…A popular task in link mining is link-based classification, which predicts an object's category based not only on its attributes but also the links it participates in and on attributes of objects linked by some path of edges [12], [16]. [17] proposed an algorithm, Biased Random Walks, to efficiently identify a large portion of the prominent individuals in the network.…”

Mutual Information to Interpret the Semantics of Anomalies in Link Mining

“…Getoor and Diehl (2005) identify a set of commonly addressed link mining tasks, which are: Object-related tasks, Link-related tasks and Graph-related tasks (which has been used in this case study).…”