17316572
Aligning Ontologies through Formal Concept Analysis
Abstract.Ontologies have been developed for a number of knowledge domains as di-verseasclinicalterminology,photocamerapartsandmicro-arraygeneexpressiondata.However,aninnatecharacteristicofthedevelopmentofontologiesisthattheyareoftencreatedbyindependentgroupsofexpertise,whichgeneratedthenecessityofmergingandaligningontologiescoveringoverlappingdomains.Manyalgorithmsandtoolshavebeenproposedformergingofontologies,butmostofthemdisregardthestructuralpropertiesofthesourceontologies,focusingmostlyonsyntacticanalysis.This article focuses on an alignment method for ontologies based on Formal ConceptAnalysis,adataanalysistechniquefoundedonlatticetheory. 1 Introduction IntheheartofSemanticWebinitiative,proposedbyTimBerners-lee[2,3],liestheideaofmachineprocessableinformation,suchthatautomatedagents,orsoftbots,couldscanthewebspaceforinformationwithaspeciﬂcmeaning.Nevertheless,theunderstandingofmeaninginWebpagesdesignedforhumansisnotaneasytaskforthepresentgenerationofsoftbotsandontologiescangreatlyassistinthisendeavour.Manyinitiativesaroundtheworldhavecreatedontologies.Someoftheseontologieswerecreatedforhighleveldescriptionoftheworld,whereasothersrepresentveryspeciﬂcsub-jects,likebreastcancer,forinstance.Sometimes,ontologiesdevelopedindependentlymayhavesomeoverlaps.TheforementionedBreastCancerOntology,forexample,mayhavecommonconceptsandrelationswithaGeneOntology.Theseoverlapsareveryimpor-tantfromthepointofviewofinformationintegration,becausethecommonontologicalentitieshavetobeidentiﬂedbeforeinformationcanbesuccessfullyintegrated.Forthisreason,mergeandalignmentofontologieshavereceivedsigniﬂcantattentionfromtheresearchcommunityinthelastsixyears.Theﬂrstimportantissueinmerge/alignmentofontologiesistherelationsymbol-meaning.Ontologiesareconstitutedofsymbols(entities)andrelationsbetweensymbols.However,inSemiotics[18]symbolshaveassociatedmeaning,whichlinksthemtotheirreferent
35048
Mining Open Source Software (OSS) Data Using Association Rules Network
The Open Source Software(OSS) movement has attracted considerable attention in the last few years. In this paper we report our results of mining data acquired from SourceForge.net, the largest open source software hosting website. In the process we introduce Association Rules Network(ARN), a (hyper)graphical model to represent a special class of association rules. Using ARNs we discover important relationships between the attributes of successful OSS projects. We verify and validate these relationships using Factor Analysis, a classical statistical technique related to Singular Value Decomposition(SVD).
17135898
The Economic Contribution of Software: An Alternative Perspective on the Productivity Paradox
The complex relationships between information technology investments and business value have been the focus of intensive research in recent years. There appears to be a discernible trend toward a more nuanced view in which the differential effects of the various categories of IT capital such as hardware, software, and their interactions with organizational factors are systematically investigated. As well, there is emerging evidence of accelerating investments in software and a greater shift toward “softwarization” (Langdon 2003) in which value addition is linked to combining flexible software with increasingly commoditized hardware. In this paper, we focus on the differential contributions of hardware and software capital and their interactions with labor capital. We use industry-level data to extend previous studies in three ways: (1) by using more recent data (1990 to 2002), (2) by focusing on IT-using industries in the private sector, and (3) by treating IT hardware and IT software as two distinct classes of IT capital. We adopt the commonly used log-linear Cobb Douglas production function approach. Our findings indicate that the impacts of software are significantly different in comparison with hardware and that the productivity benefits attributable to IT are largely due to the interactions between software and labor inputs. We conclude that software is the key to productivity growth in the IT-using world, and show that it can be used as the closest surrogate to represent business complementarities to IT in macro-level studies.
19186309
Using an Aligned Ontology to Process User Queries
Ontologies have been developed for a number of knowledge domains as diverse as clinical terminology, photo camera parts and micro-array gene expression data. However, processing user queries over a set of overlapping ontologies is not straightforward because they have often been created by independent groups of expertise, each of them adopting different configurations for ontology concepts. A project being carried out at the Brazilian Corporation of Agricultural Research has produced ontologies in sub-domains such as beef cattle, dairy cattle, sheep and beans, among others. This paper focuses on an alignment method for these ontologies based on Formal Concept Analysis, a data analysis technique founded on lattice theory, and a strategy for processing user queries.
14742091
On local pruning of association rules using directed hypergraphs
Here we propose an adaptive local pruning method for association rules. Our method exploits the exact mapping between a certain class of association rules, namely those whose consequents are singletons and backward directed hypergraphs (B-graphs). The hypergraph which represents the association rules is called an association rules network(ARN). Here we present a simple example of an ARN. We further prove several properties of the ARN and apply the results of our approach to two popular data sets.
15297691
Aligning Ontologies and Evaluating Concept Similarities
An innate characteristic of the development of ontologies is that they are often created by independent groups of expertise, which generates the necessity of merging and aligning ontologies covering overlapping domains. However, a central issue in the merging process is the evaluation of the differences between two ontologies, viz. the establishment of a similarity measure between their concepts. Many algorithms and tools have been proposed for merging of ontologies, but the majority of them disregard the structural properties of the source ontologies, focusing mostly on syntactic analysis. This article focuses on the alignment of ontologies through Formal Concept Analysis, a data analysis technique founded on lattice theory, and on the use of similarity measures to identify cross-ontology related concepts.
10894133
Octree textures
Texturing using a set of two dimensional image maps is an established and widespread practice. However, it has many limitations. Parameterizing a model in texture space can be very difficult, particularly with representations such as implicit surfaces, subdivision surfaces, and very dense or detailed polygonal meshes. This paper proposes the use of a new kind of texture based on an octree, which needs no parameterization other than the surface itself, and yet has similar storage requirements to 2D maps. In addition, it offers adaptive detail, regular sampling over the surface, and continuity across surface boundaries. The paper addresses texture creation, painting, storage, processing, and rendering with octree textures.
15437979
Why direct LDA is not equivalent to LDA
In this paper, we present counter arguments against the direct LDA algorithm (D-LDA), which was previously claimed to be equivalent to Linear Discriminant Analysis (LDA). We show from Bayesian decision theory that D-LDA is actually a special case of LDA by directly taking the linear space of class means as the LDA solution. The pooled covariance estimate is completely ignored. Furthermore, we demonstrate that D-LDA is not equivalent to traditional subspace-based LDA in dealing with the Small Sample Size problem. As a result, D-LDA may impose a significant performance limitation in general applications.
10444578
A reliable-inference framework for recognition of human actions
We present an action recognition method based on the concept of reliable inference. Our approach is formulated in a probabilistic framework using posterior class ratios to verify the saliency of an input before committing to any action classification. The framework is evaluated in the context of walking, running, and standing at multiple viewpoints and compared to ML and MAP approaches. Results examining individual silhouette images with the framework demonstrate that these actions can be reliably discriminated while discounting confusing images.
7453479
Dienst: an architecture for distributed document libraries
As one of the five universities participating in the ARPA-sponsored Computer Science Technical Report project, we at Cornell have developed a digital library architecture called Dienst. Dienst is a protocol and implementation that provides Internet access to a distributed, decentralized multi-format document collection. The collection is managed by a set of interoperating Dienst servers distributed over the Internet. These servers provide three digital library services: repositories of multi-format documents; indexes into the document collection and search engines for these indexes; and user interfaces for browsing, searching, and accessing the collection.
14448568
Sampling Representative Examples for Dimensionality Reduction and Recognition - Bootstrap Bumping LDA
We present a novel method for dimensionality reduction and recognition based on Linear Discriminant Analysis (LDA), which specifically deals with the Small Sample Size (SSS) problem in Computer Vision applications. Unlike the traditional methods, which impose specific assumptions to address the SSS problem, our approach introduces a variant of bootstrap bumping technique, which is a general framework in statistics for model search and inference. An intermediate linear representation is first hypothesized from each bootstrap sample. Then LDA is performed in the reduced subspace. Lastly, the final model is selected among all hypotheses for the best classification. Experiments on synthetic and real datasets demonstrate the advantages of our Bootstrap Bumping LDA (BB-LDA) approach over the traditional LDA based methods.