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InClose, a Fast Algorithm for Computing Formal Concepts
 the Seventeenth International Conference on Conceptual Structures
, 2009
"... Abstract. This paper presents an algorithm, called InClose, that uses incremental closure and matrix searching to quickly compute all formal concepts in a formal context. InClose is based, conceptually, on a well known algorithm called CloseByOne. The serial version of a recently published algor ..."
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Abstract. This paper presents an algorithm, called InClose, that uses incremental closure and matrix searching to quickly compute all formal concepts in a formal context. InClose is based, conceptually, on a well known algorithm called CloseByOne. The serial version of a recently published algorithm (Krajca, 2008) was shown to be in the order of 100 times faster than several wellknown algorithms, and timings of other algorithms in reviews suggest that none of them are faster than Krajca. This paper compares InClose to Krajca, discussing computational methods, data requirements and memory considerations. From experiments using several public data sets and random data, this paper shows that InClose is in the order of 20 times faster than Krajca. InClose is small, straightforward, requires no matrix preprocessing and is simple to implement. 1
Mobile Information Retrieval with Search Results Clustering: Prototypes and Evaluations
 Journal of American Society for Information Science and Technology (JASIST
, 2009
"... Web searches from mobile devices such as PDAs and cell phones are becoming increasingly popular. However, the traditional listbased search interface paradigm does not scale well to mobile devices due to their inherent limitations. In this article, we investigate the application of search results cl ..."
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Web searches from mobile devices such as PDAs and cell phones are becoming increasingly popular. However, the traditional listbased search interface paradigm does not scale well to mobile devices due to their inherent limitations. In this article, we investigate the application of search results clustering, used with some success for desktop computer searches, to the mobile scenario. Building on CREDO (Conceptual Reorganization of Documents), a Web clustering engine based on concept lattices, we present its mobile versions Credino and SmartCREDO, for PDAs and cell phones, respectively. Next, we evaluate the retrieval performance of the three prototype systems. We measure the effectiveness of their clustered results compared to a ranked list of results on a subtopic retrieval task, by means of the deviceindependent notion of subtopic reach time together with a reusable test collection built from Wikipedia ambiguous entries. Then, we make a crosscomparison of methods (i.e., clustering and ranked list) and devices (i.e., desktop, PDA, and cell phone), using an interactive informationfinding task performed by external participants. The main finding is that clustering engines are a viable complementary approach to plain search engines both for desktop and mobile searches especially, but not only, for multitopic informational queries.
Bootstrapping ontology learning for information retrieval using formal concept analysis and information anchors
 14TH INTERNATIONAL CONFERENCE ON CONCEPTUAL STRUCTURES
"... We present an innovative approach to information retrieval for domainspecific digital library collections. We use a combination of Formal Concept Analysis (FCA) and a notion of information anchors to facilitate information delivery to the end user. This approach (1) uses ranked objects in attribut ..."
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We present an innovative approach to information retrieval for domainspecific digital library collections. We use a combination of Formal Concept Analysis (FCA) and a notion of information anchors to facilitate information delivery to the end user. This approach (1) uses ranked objects in attribute concepts to facilitate topical queries for experts and expertise profiles; (2) formulates (keyword by keyword) context for concept lattice construction via a set of heuristics, including those based on information anchors for selecting descriptive phrases, (3) bootstraps the learning of domainspecific concept hierarchies using FCA, and (4) incorporates the learnt concept hierarchies and WordNet for contentbased document classification. To demonstrate the feasibility and utility of this approach, we implemented a prototype online information retrieval systemmemsworldonline.case.edu (MWOL) for the emerging engineering discipline of MEMS (microelectromechanical systems) incorporating these ideas. MWOL has been actively used by a nontrivial group of MEMS practitioners; all user queries are processed in a fraction of a second as a result of inverse indexing strategy using Berkeley DB. Voluntary user feedback using online forms has been encouraging. However, no other systems with similar features are available for a comparative study at this point.
B.S.: Formal concept discovery in semantic web data
 In: ICFCA
, 2012
"... Abstract. Semantic Web efforts aim to bring the WWW to a state in which all its content can be interpreted by machines; the ultimate goal being a machineprocessable Web of Knowledge. We strongly believe that adding a mechanism to extract and compute concepts from the Semantic Web will help to achi ..."
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Abstract. Semantic Web efforts aim to bring the WWW to a state in which all its content can be interpreted by machines; the ultimate goal being a machineprocessable Web of Knowledge. We strongly believe that adding a mechanism to extract and compute concepts from the Semantic Web will help to achieve this vision. However, there are a number of open questions that need to be answered first. In this paper we will establish partial answers to the following questions: 1) Is it feasible to obtain data from the Web (instantaneously) and compute formal concepts without a considerable overhead; 2) have data sets, found on the Web, distinct properties and, if so, how do these properties affect the performance of concept discovery algorithms; and 3) do stateoftheart concept discovery algorithms scale wrt. the number of data objects found on the Web?
On quantum statistics in data analysis
 In Proceedings of the Second Quantum Interaction Symposium (QI2008
, 2008
"... Originally, quantum probability theory was developed to analyze statistical phenomena in quantum systems, where classical probability theory does not apply, because the lattice of measurable sets is not necessarily distributive. On the other hand, it is well known that the lattices of concepts, that ..."
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Originally, quantum probability theory was developed to analyze statistical phenomena in quantum systems, where classical probability theory does not apply, because the lattice of measurable sets is not necessarily distributive. On the other hand, it is well known that the lattices of concepts, that arise in data analysis, are in general also nondistributive, albeit for completely different reasons. In his recent book, van Rijsbergen (2004) argues that many of the logical tools developed for quantum systems are also suitable for applications in information retrieval. I explore the mathematical support for this idea on an abstract vector space model, covering several forms of data analysis (information retrieval, data mining, collaborative filtering, formal concept analysis...), and roughly based on an idea from categorical quantum mechanics (Abramsky & Coecke 2004; Coecke & Pavlovic 2007). It turns out that quantum (i.e., noncommutative) probability distributions arise already in this rudimentary mathematical framework. We show that a Belltype inequality (Bell 1964) must be satisfied by the standard similarity measures, if they are used for preference predictions. The fact that already a very general, abstract version of the vector space model yields simple counterexamples for such inequalities seems to be an indicator of a genuine need for quantum statistics in data analysis.
Knowledge Discovery through creating Formal Contexts
"... This document is the author deposited version. You are advised to consult the publisher's version if you wish to cite from it. ..."
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This document is the author deposited version. You are advised to consult the publisher's version if you wish to cite from it.
Linkability Estimation Between Subjects and Message Contents Using Formal Concepts
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Facetlike Structures in Computer Science
, 2008
"... This paper discusses how facetlike structures occur as a commonplace feature in a variety of computer science disciplines as a means for structuring class hierarchies. The paper then focuses on a mathematical model for facets (and class hierarchies in general), called formal concept analysis, and ..."
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This paper discusses how facetlike structures occur as a commonplace feature in a variety of computer science disciplines as a means for structuring class hierarchies. The paper then focuses on a mathematical model for facets (and class hierarchies in general), called formal concept analysis, and discusses graphical representations of faceted systems based on this model.
Concept analysis as a formal method for menu design
 Lecture Notes in Computer Science
"... Abstract. The design and construction of navigation menus for websites have traditionally been performed manually according to the intuition of a web developer. This paper introduces a new approach, FcAWN (pronounced “fawn”) – Formal concept Analysis for Web Navigation – to assist in the design and ..."
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Abstract. The design and construction of navigation menus for websites have traditionally been performed manually according to the intuition of a web developer. This paper introduces a new approach, FcAWN (pronounced “fawn”) – Formal concept Analysis for Web Navigation – to assist in the design and generation of a coherent and logical navigation hierarchy for a set of web documents. We provide an algorithmic process for generating multilayered menu models using FcAWN and demonstrate its feasibility with an experimental case study. Our study reveals a fundamental difference between the traditional treebased menu structure and the latticebased menu structure by FcAWN: a FcAWNgenerated lattice structure is more general than a tree structure and yet is mathematically sound and uniquely suited for menu design and construction. FcAWN is the first mathematical principle for menu design and generation, providing a practical basis for humancomputer interaction. 1
Interpreting the Neural Code with Formal Concept Analysis
"... We propose a novel application of Formal Concept Analysis (FCA) to neural decoding: instead of just trying to figure out which stimulus was presented, we demonstrate how to explore the semantic relationships in the neural representation of large sets of stimuli. FCA provides a way of displaying and ..."
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We propose a novel application of Formal Concept Analysis (FCA) to neural decoding: instead of just trying to figure out which stimulus was presented, we demonstrate how to explore the semantic relationships in the neural representation of large sets of stimuli. FCA provides a way of displaying and interpreting such relationships via concept lattices. We explore the effects of neural code sparsity on the lattice. We then analyze neurophysiological data from highlevel visual cortical area STSa, using an exact Bayesian approach to construct the formal context needed by FCA. Prominent features of the resulting concept lattices are discussed, including hierarchical face representation and indications for a productofexperts code in real neurons. 1