1,043 research outputs found
Towards Collaborative Conceptual Exploration
In domains with high knowledge distribution a natural objective is to create
principle foundations for collaborative interactive learning environments. We
present a first mathematical characterization of a collaborative learning
group, a consortium, based on closure systems of attribute sets and the
well-known attribute exploration algorithm from formal concept analysis. To
this end, we introduce (weak) local experts for subdomains of a given knowledge
domain. These entities are able to refute and potentially accept a given
(implicational) query for some closure system that is a restriction of the
whole domain. On this we build up a consortial expert and show first insights
about the ability of such an expert to answer queries. Furthermore, we depict
techniques on how to cope with falsely accepted implications and on combining
counterexamples. Using notions from combinatorial design theory we further
expand those insights as far as providing first results on the decidability
problem if a given consortium is able to explore some target domain.
Applications in conceptual knowledge acquisition as well as in collaborative
interactive ontology learning are at hand.Comment: 15 pages, 2 figure
On the Usability of Probably Approximately Correct Implication Bases
We revisit the notion of probably approximately correct implication bases
from the literature and present a first formulation in the language of formal
concept analysis, with the goal to investigate whether such bases represent a
suitable substitute for exact implication bases in practical use-cases. To this
end, we quantitatively examine the behavior of probably approximately correct
implication bases on artificial and real-world data sets and compare their
precision and recall with respect to their corresponding exact implication
bases. Using a small example, we also provide qualitative insight that
implications from probably approximately correct bases can still represent
meaningful knowledge from a given data set.Comment: 17 pages, 8 figures; typos added, corrected x-label on graph
Myb proteins inhibit fibroblast transformation by v-Rel
Genes that cause cancer have been divided into two general classes – oncogenes that act in a dominant fashion to transform normal cells into a malignant state, and tumor suppressor genes that act in a dominant fashion to prevent such transformation. In this report, we demonstrate that both the v-myb retroviral oncogene, which causes leukemic transformation of hematopoietic cells, and the c-myb proto-oncogene can also function as inhibitors of fibroblast transformation by the v-rel oncogene. These results imply that the myb genes can function either as oncogenes or as tumor suppressors in different cellular contexts
Transcriptional activation by the Myb proteins requires a specific local promoter structure
AbstractThe biological effects of the cellular c-Myb and the viral v-Myb proteins are strikingly different. While c-Myb is indispensable for normal hematopoiesis, v-Myb induces acute leukemia. The v-Myb DNA-binding domain (DBD) differs from that of c-Myb mainly by deletion of the first of three repeats which correlates with efficient oncogenic transformation and a decrease in DNA-binding activity. To investigate the difference in DNA-binding and transcriptional activation, oligonucleotide selection and electrophoretic mobility shift assays were employed. The v-Myb DBD (R2R3) shows an intrinsic DNA-binding specificity for an AT-rich downstream extension of the Myb recognition element (MRE) PyAACT/GG for efficient binding to this site, whereas R1 within the c-Myb DBD allows for more flexibility for this downstream extension. Therefore, due to the presence of repeat R1, c-Myb can bind to a greater number of target sites. The intrinsic DNA-binding specificity of R2R3 is further supported with the results from in vivo transcriptional activation experiments which demonstrated that both the v-Myb and c-Myb DBDs require an extension of the MRE (motif #1) by a downstream T-stretch (motif #2) for full activity. Surprisingly, the T-stretch improves binding when present on either strand, but is required on a specific strand for transcriptional activation
Formal concept analysis and structures underlying quantum logics
A Hilbert space induces a formal context, the Hilbert formal context , whose associated concept lattice is isomorphic to the lattice of closed subspaces of . This set of closed subspaces, denoted , is important in the development of quantum logic and, as an algebraic structure, corresponds to a so-called ``propositional system'', that is, a complete, atomistic, orthomodular lattice which satisfies the covering law.
In this paper, we continue with our study of the Chu construction by introducing the Chu correspondences between Hilbert contexts, and showing that the category of Propositional Systems, PropSys, is equivalent to the category of of Chu correspondences between Hilbert contextsUniversidad de Málaga. Campus de Excelencia Internacional AndalucĂa Tech
IrF4: From Tetrahedral Compass Model to Topological Semimetal
The intersection of topology, symmetry, and magnetism yields a rich structure
of possible phases. In this work, we study theoretically the consequences of
magnetism on IrF4, which was recently identified as a possible candidate
topological nodal chain semimetal in the absence of magnetic order. We show
that the spin-orbital nature of the Ir moments gives rise to strongly
anisotropic magnetic couplings resembling a tetrahedral compass model on a
diamond lattice. The predicted magnetic ground state preserves key symmetries
protecting the nodal lines, such that they persist into the ordered phase at
the mean-field level. The consequences for other symmetry reductions are also
discussed
Discovering Implicational Knowledge in Wikidata
Knowledge graphs have recently become the state-of-the-art tool for
representing the diverse and complex knowledge of the world. Examples include
the proprietary knowledge graphs of companies such as Google, Facebook, IBM, or
Microsoft, but also freely available ones such as YAGO, DBpedia, and Wikidata.
A distinguishing feature of Wikidata is that the knowledge is collaboratively
edited and curated. While this greatly enhances the scope of Wikidata, it also
makes it impossible for a single individual to grasp complex connections
between properties or understand the global impact of edits in the graph. We
apply Formal Concept Analysis to efficiently identify comprehensible
implications that are implicitly present in the data. Although the complex
structure of data modelling in Wikidata is not amenable to a direct approach,
we overcome this limitation by extracting contextual representations of parts
of Wikidata in a systematic fashion. We demonstrate the practical feasibility
of our approach through several experiments and show that the results may lead
to the discovery of interesting implicational knowledge. Besides providing a
method for obtaining large real-world data sets for FCA, we sketch potential
applications in offering semantic assistance for editing and curating Wikidata
Clones in Graphs
Finding structural similarities in graph data, like social networks, is a
far-ranging task in data mining and knowledge discovery. A (conceptually)
simple reduction would be to compute the automorphism group of a graph.
However, this approach is ineffective in data mining since real world data does
not exhibit enough structural regularity. Here we step in with a novel approach
based on mappings that preserve the maximal cliques. For this we exploit the
well known correspondence between bipartite graphs and the data structure
formal context from Formal Concept Analysis. From there we utilize
the notion of clone items. The investigation of these is still an open problem
to which we add new insights with this work. Furthermore, we produce a
substantial experimental investigation of real world data. We conclude with
demonstrating the generalization of clone items to permutations.Comment: 11 pages, 2 figures, 1 tabl
Practical Use of Formal Concept Analysis in Service-Oriented Computing
International audiencePervasive applications are encountered in a number of settings, including smart houses, intelligent buildings or connected plants. Service-Oriented Computing is today the technology of choice for implementing and exposing resources in such environments. The selection of appropriate services at the right moment in order to compose meaningful applications is however a real issue. In this paper, we propose a FCA-based solution to this problem.We have integrated FCA algorithms in our pervasive gateways and adapted them in order to allow efficient runtime selection of heterogeneous and dynamic services. This work has been applied to realistic use cases in the scope of a European project
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