Comparing performance of algorithms for generating concept lattices

Kuznetsov, Sergei O.; Obiedkov, Sergei

doi:10.1080/09528130210164170

Cited by 398 publications

(215 citation statements)

References 12 publications

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“…A variety of algorithms are available to compute concepts and concept lattices [34], [36], [27], [37]. Given the lattice structure of the concepts a separate procedure is used to coalesce the concepts and form a new concept lattice.…”

Section: Methodsmentioning

confidence: 99%

Towards a Formal Concept Analysis Approach to Exploring Communities on the World Wide Web

Rome

Haralick

2005

Formal Concept Analysis

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Abstract. An interesting problem associated with the World Wide Web (Web) is the definition and delineation of so called Web communities. The Web can be characterized as a directed graph whose nodes represent Web pages and whose edges represent hyperlinks. An authority is a page that is linked to by high quality hubs, while a hub is a page that links to high quality authorities. A Web community is a highly interconnected aggregate of hubs and authorities. We define a community core to be a maximally connected bipartite subgraph of the Web graph.We observe that the web subgraph can be viewed as a formal context and that web communities can be modeled by formal concepts. Additionally, the notions of hub and authority are captured by the extent and intent, respectively, of a concept. Though Formal Concept Analysis (FCA) has previously been applied to the Web, none of the FCA based approaches that we are aware of consider the link structure of the Web pages. We utilize notions from FCA to explore the community structure of the Web graph. We discuss the problem of utilizing this structure to locate and organize communities in the form of a knowledge base built from the resulting concept lattice and discuss methods to reduce the complexity of the knowledge base by coalescing similar Web communities. We present preliminary experimental results obtained from real Web data that demonstrate the usefulness of FCA for improving Web search.

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Section: Methodsmentioning

confidence: 99%

Towards a Formal Concept Analysis Approach to Exploring Communities on the World Wide Web

Rome

Haralick

2005

Formal Concept Analysis

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“…Comparison of computational complexity of algorithms for generating concept lattice can be found in [11]. As stated in the paper, the total complexity of lattice generation depends on the size of input data as well as on the size of output lattice.…”

Section: Complexity Aspectsmentioning

confidence: 99%

On Social Networks Reduction

Snåšel

Horák

Kočíbová

et al. 2009

Lecture Notes in Computer Science

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Abstract. Since the availability of social networks data and the range of these data have significantly grown in recent years, new aspects have to be considered. In this paper, we use combination of Formal Concept Analysis and well-known matrix factorization methods to address computational complexity of social networks analysis and clarity of their visualization. The goal is to reduce the dimension of social network data and to measure the amount of information, which has been lost during the reduction. Presented example containing real data proves the feasibility of our approach.

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“…The construction of the lattice can be made using, for instance, the Bordat's algorithm [Bor86], which compute recursively all the existing concepts starting from the concept (∅, f (∅)), computing for each found concept the set of its subconcepts. A good review of other algorithms for Galois lattices generation can be found in [KO01] which gives also a comparison of performances.…”

Section: Words Tweetsmentioning

confidence: 99%

A Buzz and E-Reputation Monitoring Tool for Twitter Based on Galois Lattices

Cuvelier

Aufaure

2011

Conceptual Structures for Discovering Knowledge

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Abstract. In the actual interconnected world, the speed of broadcasting of information leads the formation of opinions towards more and more immediacy. Big social networks, by allowing distribution, and therefore broadcasting of information in a almost instantaneous way, also speed up the formation of opinions concerning actuality. Then, these networks are great observatories of opinions and e-reputation. In this e-reputation monitoring task, it is easy to get a set of information (web pages, blog pages, tweets,...) containing a chosen word or a set of words ( a company name, a domain of interest,...), and then we can easily search for the most used words. But a harder, but more interesting task, is to track the set of jointly used words in this dataset, because this latter contains the more shared advice about the initial searched set of words. Precisely, the exhaustive discovering of the shared properties of a collection of objects is the main task of the Galois lattices used in the Formal Concept Analysis. In this article we state clearly the characteristics, advantages and constraints of one of the more successful online social networks: Twitter. Then we detail the difficult task of tracking, on Twitter, the most forwarded information about a chosen subject. We also explain how the characteristics of Galois lattices permit to solve elegantly and efficiently this problem. But, retrieving the most used corpus of words is not enough, we have to show the results in an informative and readable manner, which is not easy when the result is a Galois Lattice. Then we propose a visualisation called topigraphic network of tags, which represent a tag cloud in a network of concepts with a topographic allegory, which permits to visualise the more important concepts found about a given search on Twitter.

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Comparing performance of algorithms for generating concept lattices

Cited by 398 publications

References 12 publications

Towards a Formal Concept Analysis Approach to Exploring Communities on the World Wide Web

Towards a Formal Concept Analysis Approach to Exploring Communities on the World Wide Web

On Social Networks Reduction

A Buzz and E-Reputation Monitoring Tool for Twitter Based on Galois Lattices

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