Joshua Shinavier
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| Joshua Shinavier (Person) [ Edit ] | |
| File:Anonymous.png | |
| Basic Description | |
| affiliation | RPI |
| occupation | Category:PhD Student |
| Contact Information | |
| General Relation | |
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Contents |
publications
total:1
2009
- Xixi Luo, Joshua Shinavier. MultiRank: Reputation Ranking for Generic Semantic Social Networks , 1st International Workshop on Motivation and Incentives on the Web,April 2009 [TW-2009-09] [ download paper ]
Projects
CSCI 6966 Advanced Semantic Web (Fall 2008)
Advanced Semantic Web: 4 presentations given
| Presentation Page | Paper Presented | Authors | URL |
|---|---|---|---|
| Joshua Shinavier Laying the foundations for a World Wide Argument Web | Laying the foundations for a World Wide Argument Web | I. Rahwan F. Zablith And C. Reed |
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6TYF-4NPG0FD-1&_user=10&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=bc463728d918e523b24d8d92adabf78e |
| Joshua Shinavier Networked Graphs | Networked Graphs: A Declarative Mechanism for SPARQL Rules, SPARQL Views and RDF Data Integration on the Web | Simon Schenk Steffen Staab |
http://www2008.org/papers/pdf/p585-schenkA4.pdf |
| Questions for Distributed Reasoning | Parallel Inferencing for OWL Knowledge Bases | R. Soma V.K. Prasanna |
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| Semantic Grounding Joshua Shinavier 20089011 | Semantic Grounding of Tag Relatedness in Social Bookmarking Systems | Ciro Cattuto Dominik Benz Andreas Hotho Gerd Stumme |
http://arxiv.org/pdf/0805.2045 |
Advanced Semantic Web: 23 questions asked
| Question Page | Question | Presentation |
|---|---|---|
| Alvaro Graves SemRank Joshua Shinavier 1 | Given that SemRank has exponential time complexity and cannot be evaluated for larger data sets, what is an empirical evaluation of the top-K algorithm likely to reveal? The authors expect that it will produce an ordering that is reasonably close to SemRank, but they go on to mention that the refraction count can only be computed at the end of the path building phase (so, the refraction count of a child path does not predict the refraction count of a parent path). Did I read this correctly? This seems important, because the top-K approximation would be critical to any real-world application of the presented technique -- SemRank alone is clearly not suitable for discovery of associations in a large graph. | Alvaro Graves SemRank |
| Alvaro Semantic Obligation Policies Joshua Shinavier 1 | The authors state that "the problem of policy concurrency is addressed by the implicit serialization of events as enforced by our streaming model". However, they also claim that the compiler is able to "plan with large numbers of event sources". When there are multiple sources involved, concurrency certainly is an issue. It is not clear how the compiled policy, a "plan" in Stream S, would go about combining events from multiple sources. Under what conditions can event descriptions from two different sources serve as input to be matched by a single event pattern? | Alvaro Semantic Obligation Policies |
| AnkeshSep11JoshuaShinavier1 | What is the reason for basing "capabilities" on predicates (exclusively)? Ignoring the details of the implementation, there are other ways in which we might want to partition a distributed data set (e.g. by assigning quads to data sources based on their named graph component. In this case, a capability might consist of a number of named graphs in which the query planner can expect to find statements). | Ankesh Sep11 |
| Asma Ounnas Semantic Social Networks Presentation Joshua Shinavier 1 | This paper presents a collection of techniques for mapping user-generated tags to Wikipedia categories. More generally, it presents a technique for aggregating user-generated tags from accounts in multiple services and generating a user profile. However, it's not clear what we gain from these other components. The account correlation component of the architecture is intended to capture different aspects of the user's interests, but doesn't seem essential to the technique. The generation of a FOAF file as the end result of profile generation seems a little arbitrary. Would the paper have benefited from a discussion of how the generated profile can ultimately be used to provide benefit to the user (e.g. by mapping interests back to original tags in each of the source web services and using these for recommendation)? | Asma Ounnas Semantic Social Networks Presentation |
| CommunityBasedMappingSep11JoshuaShinavier1 | This may be beyond the scope of the tool, but it might be useful to allow users to create mappings not only at the concept level, but also at the ontology level. For instance, a user might want to simply assert that two ontologies are similar or that they cover a similar domain, rather than picking out individual concepts to map. | Community-basedMapping Shangguan 0911 |
| Debbie Journal Presentation Joshua Shinavier 1 | The ability to infer broader/narrower relationships among tags seems promising, but it's not clear to me how the author achieves this using the presented framework. Some additional discussion of the technique involved would help to understand the significance of the experimental results. | Debbie Journal Presentation |
| Debbie Rank Typed Graph Walks Presentation Joshua Shinavier 1 | Debbie Rank Typed Graph Walks Presentation | |
| Giovanni Numeric Reasoning Joshua Shinavier 1 | It makes sense that the technique presented could cut down on table joins in many cases. However, the mapping from "special" triple patterns (e.g. in a SPARQL query otherwise requiring logical reasoning) to PostgreSQL is not discussed in detail. Is it straightforward? | Giovanni Numeric Reasoning |
| Gregory Todd Williams Graph Summaries Joshua Shinavier 1 | Is Example 2 correct? The edge type (5, 1, 4) appears three times in the patterns of Figure 4a, while it appears only twice in Figure 4b. Instead, edge type (6, 3, 2) appears once too often in Figure 4b, in place of (5, 1, 4). | Gregory Todd Williams Graph Summaries |
| Gregory Todd Williams SPARQL BGP Optimization Presentation Joshua Shinavier 1 | What is it about the presented approach which makes it appropriate only for in-memory RDF repositories? I don't understand why the same arguments and techniques would not apply to disk-based stores. | Gregory Todd Williams SPARQL BGP Optimization Presentation |
| James Journal Presentation Joshua Shinavier 2 | The author shows how Flink might be used for social network analysis, then note that he plans to report on the results of his study of the SW community in a future publication. What are these results? Has Flink led to any future (post-2005) work? | James Journal Presentation |
| James Journal Presentation Joshua Shinavier 1 | In the introduction, it is stated that user profiles in centralized social networking services "cannot be exported in machine processable formats". Why not? As is mentioned in the paper, there are several large producers of FOAF, for example, my.opera.com. It's not necessarily true that such systems "do not let users to control the information they provide on their own terms", either. In fact, centralized services may be some of the best potential sources for well-formed Semantic Web data. | James Journal Presentation |
| James Michaelis Provenance Model Joshua Shinavier 1 | More of a comment than a question, but as a formal description of the Open Provenance Model, this paper contains a lot of material which seems unclear, unnecessary or inconsistent. For example, the "rules" of the Provenance Graph definition: in rules 2 through 5, what does it mean to "list the accounts" an item belongs to? Rule 12 (union and intersection of legal account views) is redundant as it follows from previous rules. Does rule 15 imply that an OPM graph with only one account view cannot be a provenance graph (because that would require a legal pair of views)? Rule 17 (provenance graphs do not need time annotations) seems superfluous as it has already been stated that time information is optional. Section 5 (Timeless Formal Model) is similar. In rule 8, what does the union or intersection of two graphs mean, when a graph is defined as a tuple, not as a set? Apart from the style of the paper, the fact that the authors do not try to explain why this particular model was chosen, what it is good for, is frustrating. | James Michaelis Provenance Model |
| Jesse Weaver RDF Management Approaches Joshua Shinavier 1 | Query 9 of SP2Bench is said to be impossible to evaluate in the purely relational case, on account of an unbound predicate. This being the case, how was query 10 evaluated, which also contains an unbound predicate that (unlike in query 3) cannot be resolved by first evaluating a FILTER expression? I must admit that I don't see how the member2, member3, and member4 variables in query 7 are resolved, either. | Jesse Weaver RDF Management Approaches |
| Jiao Concept Mapping Joshua Shinavier 1 | To what extent did the choice of a classifier technique (Markov networks) affect the results of the various experiments? Would it have been possible to apply another variety of classifier (e.g. support vector machines) with better results for some experiments? | Jiao Concept Mapping |
| Joshua Taylor Discovering Simple Mappings Joshua Shinavier 1 | A basic premise of this work is that finding mappings between RDB schemas and ontologies is an effective way to achieve interoperability on the Web. Is this in fact the case? In what circumstances would discovering mappings between a given RDB schema and a given ontology be worthwhile? In such a scenario, are there advantages to the presented technique, versus translating the RDB schema to an ontology (e.g. using a tool like D2R) and then using existing ontology-to-ontology mapping techniques? Do the sources mentioned in the section on Related Work motivate this solution? | Joshua Taylor presents Discovering Simple Mappings Between Relational Database Schemas and Ontologies |
| Medha GRIN Presentation Joshua Shinavier 1 | Apart from introducing a novel indexing mechanism for RDF, this paper also introduces an extension to SPARQL, in the form of P-path edges. However, it's not clear why P-paths are necessary, nor why the authors chose to model them as they did (as sets of predicates, as opposed to, say, sequences of predicates, regular expressions, or other formalisms used in proposed path extensions to SPARQL). They obviously play no part in the average query times which the authors use to compare GRIN with Jena, Sesame and RDFBroker, as these tools only deal with standard SPARQL queries. Why are the 20 non-standard TAP and ChefMoz queries mentioned at all? Can anything be said about GRIN's performance for these queries? The authors claim that "GRINAnswer is *often faster* than Jena, Sesame and RDFBroker for *certain types* of graph-based queries", which seems like a weak statement, especially since we're not told which queries these are. Do the advantages of GRIN have more to do with efficient evaluation of standard SPARQL queries, or with the ability to evaluate path-based queries of the variety supported by GRIN? | Medha GRIN Presentation |
| Medha Journal Presentation Joshua Shinavier 1 | It would be helpful to see a time complexity analysis of the proposed technique. The authors state that a graph of 40,000 nodes and 475,000 edges takes around two minutes to analyze on a typical PC, which is better than one might expect. But now, how about a graph with a million edges? Does the algorithm take four minutes or four years to produce a result? | Medha Journal Presentation |
| Medha Journal Presentation Joshua Shinavier 2 | To what extent does this technique depend on the nature of the MRN under analysis? Are there meaningful networks (particularly, networks of interest to the intelligence domain) for which the diversity of simple paths makes it impossible to identify "abnormal" nodes? | Medha Journal Presentation |
| NSPARQL Jesse Weaver 20080911 Joshua Shinavier 1 | One of the main points of this paper is that nested regular expressions can be evaluated efficiently, in linear time w.r.t. the size of the graph and to the length of the expression. From a practical point of view, though, is this really efficient? One of the nice things about traversal-based algorithms is that, depending on the topology of the graph, their performance may be more or less independent the actual size of the graph. The proposed evaluation strategy, in contrast, appears to require a massive global calculation for each step in a path expression, e.g. upwards of one billion operations for a simple one-step path from a node to its immediate neighbors in a large, billion-node graph. | NSPARQL Jesse Weaver 20080911 |
| Shangguan Journal CNLPresentation Joshua Shinavier 1 | I am inclined to disagree with the authors' statement that "what is urgently required is a high-level interface language to the Semantic Web...", with which they motivate their innovation. Is it necessary for novice Web users to express RDF statements/graphs directly? It seems that novice users should deal with RDF only indirectly, through use of special-purpose interfaces which generate metadata on their behalf. Furthermore, the idea of an interface language is misleading, as the CNL tool (the "look-ahead text editor") is actually a GUI in disguise. The CNL expressions alone evidently cannot be decompiled to RDF. | Shangguan Journal CNLPresentation |
| Shangguan Managing Ontologies Joshua Shinavier 1 | The authors mention that Ontolingua supports cyclical ontology inclusion. Is this true of KAON? Does the mechanism of change filtering make it possible to propagate changes through an ontology cycle and its dependent ontologies (that is, without runaway recursion)? | Shangguan Managing Ontologies |
| Zhao2004using presented by Tim Lebo 9 oct 2008 Joshua Shinavier 1 | I'm also curious about the choice of LSIDs as identifiers. Is there anything about the LSID system which could not be achieved more simply (i.e. without an additional standard, additional tools including SOAP services and clients) using HTTP? The AuthorityID might as well be the domain name portion of an HTTP URI. The authority server then optionally redirects to the resolution service. The authors mention only querying and data retrieval, but perhaps a resolution service also provides metadata management services which require the RPC functionality of SOAP (and/or other protocols)? In that case, is a single client expected to be able to communicate with a variety of resolution services, using diverse protocols? | Zhao2004using presented by Tim Lebo 9 oct 2008 |
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