Fuzzy and rough formal concept analysis: a survey

Formal Concept Analysis (FCA) is a mathematical technique that has been extensively applied to Boolean data in knowledge discovery, information retrieval, web mining, etc. applications. During the past years, the research on extending FCA theory to cope with imprecise and incomplete information made significant progress. In this paper, we give a systematic overview of the more than 120 papers published between 2003 and 2011 on FCA with fuzzy attributes and rough FCA. We applied traditional FCA as a text-mining instrument to 1072 papers mentioning FCA in the abstract. These papers were formatted in pdf files and using a thesaurus with terms referring to research topics, we transformed them into concept lattices. These lattices were used to analyze and explore the most prominent research topics within the FCA with fuzzy attributes and rough FCA research communities. FCA turned out to be an ideal metatechnique for representing large volumes of unstructured texts

Formal concept analysis in knowledge processing: a survey on applications

This is the second part of a large survey paper in which we analyze recent literature on Formal Concept Analysis (FCA) and some closely related disciplines using FCA. We collected 1072 papers published between 2003 and 2011 mentioning terms related to Formal Concept Analysis in the title, abstract and keywords. We developed a knowledge browsing environment to support our literature analysis process. We use the visualization capabilities of FCA to explore the literature, to discover and conceptually represent the main research topics in the FCA community. In this second part, we zoom in on and give an extensive overview of the papers published between 2003 and 2011 which applied FCA-based methods for knowledge discovery and ontology engineering in various application domains. These domains include software mining, web analytics, medicine, biology and chemistry data

Text mining scientific papers: a survey on FCA-based information retrieval research

Formal Concept Analysis (FCA) is an unsupervised clustering technique and many scientific papers are devoted to applying FCA in Information Retrieval (IR) research. We collected 103 papers published between 2003-2009 which mention FCA and information retrieval in the abstract, title or keywords. Using a prototype of our FCA-based toolset CORDIET, we converted the pdf-files containing the papers to plain text, indexed them with Lucene using a thesaurus containing terms related to FCA research and then created the concept lattice shown in this paper. We visualized, analyzed and explored the literature with concept lattices and discovered multiple interesting research streams in IR of which we give an extensive overview. The core contributions of this paper are the innovative application of FCA to the text mining of scientific papers and the survey of the FCA-based IR research

Homophily Evolution in Online Networks: Who Is a Good Friend and When?

Homophily is considered by network scientists as one of the major mechanisms of social network formation. However, the role of dynamic homophily in the network growth process has not been investigated in detail yet. In this paper, we estimate the role of homophily by various attributes at different stages of online network formation process. We consider the process of online friendship formation in the Vkontakte social networking site among first-year students at a Russian university. We reveal that at the beginning of the network formation a similarity in gender and score in entrance exams plays the key role, while by the end of network establishment period the role of the same group affiliation becomes more important. We explain the results with the tendency of students to follow different strategies to control the information flow in their social environment

Homophily Evolution in Online Networks: Who Is a Good Friend and When?

Homophily is considered by network scientists as one of the major mechanisms of social network formation. However, the role of dynamic homophily in the network growth process has not been investigated in detail yet. In this paper, we estimate the role of homophily by various attributes at different stages of online network formation process. We consider the process of online friendship formation in the Vkontakte social networking site among first-year students at a Russian university. We reveal that at the beginning of the network formation a similarity in gender and score in entrance exams plays the key role, while by the end of network establishment period the role of the same group affiliation becomes more important. We explain the results with the tendency of students to follow different strategies to control the information flow in their social environment

Who are my ancestors? : retrieving family relationships from historical texts

This paper presents an approach for automatically retrieving family relationships from a real-world collection of Dutch historical notary acts. We aim to retrieve relationships like husband - wife, parent - child, widow of, etc. Our approach includes person names extraction, reference disambiguation, candidate generation and family relationship prediction. Since we have a limited amount of training data, we evaluate different feature configurations based on the n-gram analysis. The best results were obtained by using a combination of bi-grams and trigrams of words together with the distance in words between two names. We evaluate our results for each type of the relationships in terms of precision, recall and f - score