http://www.bibsonomy.org/burst/user/stefanoBibSonomy BuRST Feed for /user/stefano2008-07-21T01:43:17+02:00http://www.bibsonomy.org/bibtex/2fac55b968016249370415f8ffd0f8b93/stefanostefano2008-06-26T13:30:14+02:00navigation hci spatial reasoning <span style="color:#555555;">S. <a href="http://www.bibsonomy.org/author/Jul">Jul</a> </span><em>The University of Michigan, </em>(<em>2004</em>)Thu Jun 26 13:30:14 CEST 2008{From Brains to Branch Points: Cognitive Constraints in Navigational Design}2004navigation hci spatial reasoning http://www.bibsonomy.org/bibtex/284bddefef6a966d2b9e9f2b0ccf5fa12/stefanostefano2008-06-26T13:29:42+02:00nlp spatial neuroscience reasoning <span style="color:#555555;">D. <a href="http://www.bibsonomy.org/author/Tranel">Tranel</a> and D. <a href="http://www.bibsonomy.org/author/Kemmerer">Kemmerer</a> </span><em>Cognitive Neuropsychology</em><em>21(7):719--749</em>(<em>2004</em>)Thu Jun 26 13:29:42 CEST 2008Cognitive Neuropsychology7719--749{Neuroanatomical correlates of locative prepositions}212004nlp spatial neuroscience reasoning The kappa statistichttp://www.bibsonomy.org/bibtex/27f2f0f656b9fce77906c0857e15fee68/stefanostefano2008-06-03T22:07:05+02:00statistics nlp <span style="color:#555555;">B. <a href="http://www.bibsonomy.org/author/Di Eugenio">Di Eugenio</a> and M. <a href="http://www.bibsonomy.org/author/Glass">Glass</a> </span><em>Computational Linguistics</em><em>30(1):95--101</em>(<em>2004</em>)Tue Jun 03 22:07:05 CEST 2008Cambridge, MA, USAComputational Linguistics195--101The kappa statistic: a second look302004statistics nlp In recent years, the kappa coefficient of agreement has become the de facto standard for evaluating intercoder agreement for tagging tasks. In this squib, we highlight issues that affect κ and that the community has largely neglected. First, we discuss the assumptions underlying different computations of the expected agreement component of κ. Second, we discuss how prevalence and bias affect the κ measure.IEEEXplore# Games with a Purpose for the Semantic Webhttp://www.bibsonomy.org/bibtex/21543b32383133720ed69e96d6c1bc088/stefanostefano2008-06-02T13:55:30+02:00crowdsourcing semanticweb learning <span style="color:#555555;">Katharina <a href="http://www.bibsonomy.org/author/Siorpaes">Siorpaes</a> and Martin <a href="http://www.bibsonomy.org/author/Hepp">Hepp</a> </span>(<em>2008</em>)Mon Jun 02 13:55:30 CEST 2008Intelligent Systems, IEEE50-60Games with a Purpose for the Semantic Web232008crowdsourcing semanticweb learning Weaving the Semantic Web requires that humans contribute their labor and judgment for extending and updating formal knowledge structures. Key tasks in evolving the current Web to a Semantic Web include discovering and specifying semantic relationships between multiple ontologies and annotating textual or multimedia information. However, whereas the Web 2.0 movement is fueled by an unprecedented number of contributions from Web users, there's a substantial lack of user involvement in weaving the heavyweight Semantic Web. One cause of this lack of involvement is a lack of proper incentive structures. Hiding the tasks involved in weaving the Semantic Web behind online multiplayer games presents the tasks as fun and intellectually challenging entertainment. A series of OntoGame prototypes support the full life cycle of realizing the Semantic Web. These games adopt Luis von Ahn's "games with a purpose" concept&#x02014;that is, presenting a task as an online game can motivate many people to work on this task, and for free. Preliminary results suggest that users are willing to spend substantial time playing the OntoGames. In addition, a setting in which users must propose a solution to a conceptual-modeling task such that it will most likely be consensual with an unknown game partner produces high-quality semantic data.http://www.bibsonomy.org/bibtex/24f6312c170fb128edb1a60520a8fbe2d/stefanostefano2008-05-25T10:16:02+02:003D analysis semantics <span style="color:#555555;">Vikash Ravi <a href="http://www.bibsonomy.org/author/Goel">Goel</a> and Roy K. <a href="http://www.bibsonomy.org/author/Greenberg">Greenberg</a> and Donald P. <a href="http://www.bibsonomy.org/author/Greenberg">Greenberg</a> </span><em>IEEE Computer Graphics and Applications</em><em>28(3):76-86</em>(<em>2008</em>)Sun May 25 10:16:02 CEST 2008Los Alamitos, CA, USAIEEE Computer Graphics and Applications376-86Automated Vascular Geometric Analysis of Aortic Aneurysms2820083D analysis semantics http://www.bibsonomy.org/bibtex/2857e36e6ff715631442e10ad9780aa95/stefanostefano2008-05-25T10:15:33+02:00generative design <span style="color:#555555;">Jason P. <a href="http://www.bibsonomy.org/author/Weber">Weber</a> </span><em>IEEE Computer Graphics and Applications</em><em>28(3):67-75</em>(<em>2008</em>)Sun May 25 10:15:33 CEST 2008Los Alamitos, CA, USAIEEE Computer Graphics and Applications367-75Fast Simulation of Realistic Trees282008generative design http://www.bibsonomy.org/bibtex/2a9ee3f9f94e1214b8ed0b344ea2950df/stefanostefano2008-05-25T10:15:04+02:00generative analysis architecture <span style="color:#555555;">Dieter <a href="http://www.bibsonomy.org/author/Finkenzeller">Finkenzeller</a> </span><em>IEEE Computer Graphics and Applications</em><em>28(3):58-66</em>(<em>2008</em>)Sun May 25 10:15:04 CEST 2008Los Alamitos, CA, USAIEEE Computer Graphics and Applications358-66Detailed Building Facades282008generative analysis architecture http://www.bibsonomy.org/bibtex/208dc676939ff6d05efa4ad42814b753e/stefanostefano2008-05-25T09:49:39+02:003D semanticweb <span style="color:#555555;">Erick <a href="http://www.bibsonomy.org/author/Mendez">Mendez</a> and Gerhard <a href="http://www.bibsonomy.org/author/Schall">Schall</a> and Sven <a href="http://www.bibsonomy.org/author/Havemann">Havemann</a> and Sebastian <a href="http://www.bibsonomy.org/author/Junghanns">Junghanns</a> and Dieter <a href="http://www.bibsonomy.org/author/Fellner">Fellner</a> and Dieter <a href="http://www.bibsonomy.org/author/Schmalstieg">Schmalstieg</a> </span><em>IEEE Computer Graphics and Applications</em><em>28(3):48-57</em>(<em>2008</em>)Sun May 25 09:49:39 CEST 2008Los Alamitos, CA, USAIEEE Computer Graphics and Applications348-57Generating Semantic 3D Models of Underground Infrastructure2820083D semanticweb SpringerLink - Book Chapterhttp://www.bibsonomy.org/bibtex/22bec0e589a3137f4224a197b83e3a9d9/stefanostefano2008-05-22T15:39:43+02:00knowledge geometry conversion <span style="color:#555555;">Philip <a href="http://www.bibsonomy.org/author/Todd">Todd</a> </span><em>Automated Deduction in Geometry</em>(<em>2007</em>)Thu May 22 15:39:43 CEST 2008Automated Deduction in Geometry189--202Geometry Expressions: A Constraint Based Interactive Symbolic Geometry System2007knowledge geometry conversion Real Euclidean geometry is a basic mathematical dialect, not only of high school students, but also of mechanical engineers, graphics programmers, architects, surveyors, machinists, and many more. In this paper, we present ”Geometry Expressions”:an interactive symbolic geometry package. The aim of the software is to generate algebraic formulas from geometry. It is afurther intention of the software that the model should be entered interactively in a style which is convenient to both thegeometry consumer groups identified above.http://www.bibsonomy.org/bibtex/265912140eb13fc39adf2b3b690f06c57/stefanostefano2008-05-22T15:38:44+02:00nlp emotions logic knowledge <span style="color:#555555;">Jerry Hobbs &amp; Andrew <a href="http://www.bibsonomy.org/author/Gordon">Gordon</a> </span>(<em>2008</em>)Thu May 22 15:38:44 CEST 2008Deep Lexical Semantics of Emotions2008nlp emotions logic knowledge We understand discourse so well because we know so much. If we are to have natural language understanding systems that are able to deal with texts with emotional content, we must encode knowledge of human emotions for use in the systems. In particular, we must equip the system with a formal version of people's implicit theory of how emotions mediate between what they experience and what they do, and rules that link the theory with words and phrases in the emotional lexicon.http://www.bibsonomy.org/bibtex/222be0cdbc877ef0a971aefa4a257d6b4/stefanostefano2008-03-27T06:36:13+01:00semanticweb privacy <span style="color:#555555;">Michael <a href="http://www.bibsonomy.org/author/Nagenborg">Nagenborg</a> </span><em>Social Semantic Web, </em><em>Springer Verlag, </em>(<em>2008</em>)Thu Mar 27 06:36:13 CET 2008Social Semantic WebPrivacy im Social Semantic Web2008semanticweb privacy http://www.bibsonomy.org/bibtex/21bfb5f33156769d97d22bf8d5b4369dc/stefanostefano2008-03-25T17:26:10+01:00ontologies metrics distance similarity <span style="color:#555555;">Alexander <a href="http://www.bibsonomy.org/author/Borgida">Borgida</a> and Thomas <a href="http://www.bibsonomy.org/author/Walsh">Walsh</a> and Haym <a href="http://www.bibsonomy.org/author/Hirsh">Hirsh</a> </span><em>Proceedings of the 2005 International Workshop on Description Logics (DL2005), July 26-28, 2005, Edinburgh, Scotland, UK, </em><em>volume147ofCEUR Workshop Proceedings, </em><em>CEUR-WS.org, </em>(<em>2005</em>)Tue Mar 25 17:26:10 CET 2008Proceedings of the 2005 International Workshop on Description Logics (DL2005), July 26-28, 2005, Edinburgh, Scotland, UKCEUR Workshop ProceedingsTowards Measuring Similarity in Description Logics.1472005ontologies metrics distance similarity SpringerLink - Book Chapterhttp://www.bibsonomy.org/bibtex/2ed5a3f62e68f6cdf12826847ac008422/stefanostefano2008-03-25T15:48:35+01:00mereology reasoning spatial <span style="color:#555555;">Max <a href="http://www.bibsonomy.org/author/Egenhofer">Egenhofer</a> and Maria <a href="http://www.bibsonomy.org/author/Vasardani">Vasardani</a> </span><em>Spatial Information Theory</em>(<em>2007</em>)Tue Mar 25 15:48:35 CET 2008Spatial Information Theory303--320Spatial Reasoning with a Hole2007mereology reasoning spatial Cavities in spatial phenomena require geometric representations of regions with holes. Existing models for reasoning over topological relations either exclude such specialized regions (9-intersection) or treat them indistinguishably from regionswithout holes (RCC-8). This paper highlights that inferences over a region with a hole need to be made separately from, andin addition to, the inferences over regions without holes. First the set of 23 topological relations between a region anda region with a hole is derived systematically. Then these relations’ compositions over the region with the hole are calculatedso that the inferences can be compared with the compositions of the topological relations over regions without holes. For266 out of the 529 compositions the results over the region with the hole were more detailed than the corresponding resultsover regions without holes, with 95 of these refined cases providing even a unique result. In 27 cases, this refinement upto uniqueness compares with a completely undetermined inference for the relations over regions without holes.http://www.bibsonomy.org/bibtex/27489a4e2594e6ec10048b740bcccb34c/stefanostefano2008-03-25T15:25:12+01:00distance ontologies metric <span style="color:#555555;">R. <a href="http://www.bibsonomy.org/author/Rada">Rada</a> and H. <a href="http://www.bibsonomy.org/author/Mili">Mili</a> and E. <a href="http://www.bibsonomy.org/author/Bicknell">Bicknell</a> and M. <a href="http://www.bibsonomy.org/author/Blettner">Blettner</a> </span>(<em>1989</em>)Tue Mar 25 15:25:12 CET 2008IEEE Transactions on Systems, Man and Cybernetics17-30Development and application of a metric on semantic nets191989distance ontologies metric Motivated by the properties of spreading activation and conceptual distance, the authors propose a metric, called distance, on the power set of nodes in a semantic net. Distance is the average minimum path length over all pairwise combinations of nodes between two subsets of nodes. Distance can be successfully used to assess the conceptual distance between sets of concepts when used on a semantic net of hierarchical relations. When other kinds of relationships, like `cause', are used, distance must be amended but then can again be effective. The judgements of distance significantly correlate with the distance judgements that people make and help to determine whether one semantic net is better or worse than another. The authors focus on the mathematical characteristics of distance that presents novel cases and interpretations. Experiments in which distance is applied to pairs of concepts and to sets of concepts in a hierarchical knowledge base show the power of hierarchical relations in representing information about the conceptual distance between conceptshttp://www.bibsonomy.org/bibtex/2283b48fc45896ba27af6d3ad492128f8/stefanostefano2008-03-22T09:19:17+01:00social networks cognition <span style="color:#555555;">Terry <a href="http://www.bibsonomy.org/author/Stewart">Stewart</a> and Robert L. <a href="http://www.bibsonomy.org/author/West">West</a> and Robert <a href="http://www.bibsonomy.org/author/Coplan">Coplan</a> </span>(<em>2006</em>)Sat Mar 22 09:19:17 CET 2008Distributed Factors in the Development of Popularity (or 'Why Doesn't Anybody Like Me?')2006social networks cognition Individual factors by no means completely account for individual popularity within a group structure. To begin to explain the majority of the variance, we must investigate the hypothesis that popularity is strongly influenced by the dynamics of group interactions. Here, we present a computational model of peer interaction that allows us to investigate the influence of different distributed factors. In constructing the model, we discovered that certain elements are vital for the simulation to produce data that matches the observed patterns in real social groups. We found that the internal representation of how much agents like each other must be discrete, that judgements should be made relative to behavioural expectations, and that models do not require variation in the initial state of the agents to produce realistic individual differences in popularity. Our result is a set of models with psychologically realistic attributes. When simulated, these models result in popularity data that cannot be reliably distinguished from real life data. Since these models capture the essential dynamics of the social group interaction, they can form the basis for understanding how interaction within the group influences individuals to become popular or rejected. http://www.bibsonomy.org/bibtex/2d2c7248eebdb8ac8204c3f1bfa059df4/stefanostefano2008-03-22T09:14:39+01:00naming coordination linguistics games <span style="color:#555555;">Q. <a href="http://www.bibsonomy.org/author/Lu">Lu</a> and G. <a href="http://www.bibsonomy.org/author/Korniss">Korniss</a> and B. K. <a href="http://www.bibsonomy.org/author/Szymanski">Szymanski</a> </span><em>Phys. Rev. E</em><em>77(1):016111</em>(<em>2008</em>)Sat Mar 22 09:14:39 CET 2008Phys. Rev. E1016111Naming games in two-dimensional and small-world-connected random geometric networks772008naming coordination linguistics games SpringerLink - Buchkapitelhttp://www.bibsonomy.org/bibtex/227c7357d3337d890fef53168dce9ed33/stefanostefano2008-03-22T08:43:23+01:00datamining search machine_learning <span style="color:#555555;">Ricardo <a href="http://www.bibsonomy.org/author/Baeza-Yates">Baeza-Yates</a> and Liliana <a href="http://www.bibsonomy.org/author/Calderón-Benavides">Calder&#243;n-Benavides</a> and Cristina <a href="http://www.bibsonomy.org/author/González-Caro">Gonz&#225;lez-Caro</a> </span><em>String Processing and Information Retrieval</em>(<em>2006</em>)Sat Mar 22 08:43:23 CET 2008String Processing and Information Retrieval98--109The Intention Behind Web Queries2006datamining search machine_learning The identification of the user’s intention or interest through queries that they submit to a search engine can be very useful to offer them more adequate results. In this work we present a framework for the identification of user’s interest in an automaticway, based on the analysis of query logs. This identification is made from two perspectives, the objectives or goals of auser and the categories in which these aims are situated. A manual classification of the queries was made in order to havea reference point and then we applied supervised and unsupervised learning techniques. The results obtained show that fora considerable amount of cases supervised learning is a good option, however through unsupervised learning we found relationshipsbetween users and behaviors that are not easy to detect just taking the query words. Also, through unsupervised learning weestablished that there are categories that we are not able to determine in contrast with other classes that were not consideredbut naturally appear after the clustering process. This allowed us to establish that the combination of supervised and unsupervisedlearning is a good alternative to find user’s goals. From supervised learning we can identify the user interest given certainestablished goals and categories; on the other hand, with unsupervised learning we can validate the goals and categories used,refine them and select the most appropriate to the user’s needs.MR: Selected Matches for: Citations of 907587http://www.bibsonomy.org/bibtex/2da6eae2bd10d4f58596b6e81f484a5a0/stefanostefano2008-03-22T08:40:47+01:00optima NK search <span style="color:#555555;">Richard <a href="http://www.bibsonomy.org/author/Durrett">Durrett</a> and Vlada <a href="http://www.bibsonomy.org/author/Limic">Limic</a> </span><em>Ann. Probab.</em><em>31(4):1713--1753</em>(<em>2003</em>)Sat Mar 22 08:40:47 CET 2008Ann. Probab.41713--1753Rigorous results for the {$NK$} model312003optima NK search MR: Selected Matches for: Citations of 907587http://www.bibsonomy.org/bibtex/2267486ea961568d9b48e14accfc4dd5c/stefanostefano2008-03-22T08:39:53+01:00NK optima search <span style="color:#555555;">Hemanshu <a href="http://www.bibsonomy.org/author/Kaul">Kaul</a> and Sheldon H. <a href="http://www.bibsonomy.org/author/Jacobson">Jacobson</a> </span><em>Math. Program.</em><em>106(2, Ser. A):319--338</em>(<em>2006</em>)Sat Mar 22 08:39:53 CET 2008Math. Program.2, Ser. A319--338Global optima results for the {K}auffman {$NK$} model1062006NK optima search MR: Selected Matches for: Citations of 907587http://www.bibsonomy.org/bibtex/24d5724ca0e8b1584ba0766262c13b848/stefanostefano2008-03-22T08:39:24+01:00search NK optima <span style="color:#555555;">Hemanshu <a href="http://www.bibsonomy.org/author/Kaul">Kaul</a> and Sheldon H. <a href="http://www.bibsonomy.org/author/Jacobson">Jacobson</a> </span><em>Math. Program.</em><em>108(2-3, Ser. B):475--494</em>(<em>2006</em>)Sat Mar 22 08:39:24 CET 2008Math. Program.2-3, Ser. B475--494New global optima results for the {K}auffman {$NK$} model: handling dependency1082006search NK optima