Browsing Semi-Structured Texts on the Web Using Formal Concept Analysis

Cole, Richard; Amardeilh, Florence; Eklund, Peter

doi:10.1007/978-3-662-07952-2_11

Cited by 14 publications

(9 citation statements)

References 8 publications

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“…Text processing is another typical application of FCA including analysis of text corpora in tourism, finance and real estate adverts (Cimiano et al 2005;Cole and Eklund 2001) as well as knowledge discovery from databases, document and email repositories Stumme et al 1998;Cole et al 2003), content based retrieval (Jay et al 2008 FCA has also been used to explore biological data. These applications include the analysis of gene expression data (Kaytoue et al 2009(Kaytoue et al , 2011, the identification of biomarkers for breast cancer (Motameny et al 2008), enzyme classification (Coste et al 2014) and the tracking of ecological traits within particular species (Bertaux et al 2009).…”

Section: Formal Concept Analysismentioning

confidence: 99%

Creating corroborated crisis reports from social media data through formal concept analysis

et al. 2016

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During a crisis citizens reach for their smart phones to report, comment and explore information surrounding the crisis. These actions often involve social media and this data forms a large repository of real-time, crisis related information. Law enforcement agencies and other first responders see this information as having untapped potential. That is, it has the capacity extend their situational awareness beyond the scope of a usual command and control centre. Despite this potential, the sheer volume, the speed at which it arrives, and unstructured nature of social media means that making sense of this data is not a trivial task and one that is not yet satisfactorily solved; both in crisis management and beyond. Therefore we propose a multi-stage process to extract meaning from this data that will provide relevant and near real-time information to command and control to assist in decision support. This process begins with the capture of real-time social media data, the development of specific LEA and crisis focused taxonomies for categorisation and entity extraction, the application of formal concept analysis for aggregation and corroboration and the presentation of this data via map-based and other visualisations. We demonstrate that this novel use of formal concept analysis in combination with context-based entity extraction has the potential to inform law enforcement and/or humanitarian responders about on-going crisis events using social media data in the context of the 2015 Nepal earthquake.

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Section: Formal Concept Analysismentioning

confidence: 99%

Creating corroborated crisis reports from social media data through formal concept analysis

et al. 2016

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“…Several FCA based systems were developed for analyzing and exploring these search results. The development of this software is based on earlier research on retrieval of information from semi-structured texts (Cole et al 2001, Cole et al 2000. The CREDO system then builds an iceberg lattice which is represented as a tree and can be interactively explored by the user.…”

Section: Web and Email Retrievalmentioning

confidence: 99%

Advances in Data Mining. Applications and Theoretical Aspects

Poelmans¹,

Ignatov²,

Viaene³

et al. 2012

Lecture Notes in Computer Science

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“…In principle, partial views can be applied also to one-valued contexts by vertically slicing the context table (an example is described in [47]), but in the latter case it may be more difficult to select subcontexts that bear value, or just meaning. In fact, some of the most interesting applications have been developed in domains characterized by semistructured data, such as those for searching collections of emails ( [17], [16]) or for analysing real-estate data extracted from the web [15].…”

Section: Combining Multiple Views Of Semi-structured Datamentioning

confidence: 99%