Diana Maynard

The Semantic Web - ISWC 2009

Research Track.- Queries to Hybrid MKNF Knowledge Bases through Oracular Tabling.- Automatically Constructing Semantic Web Services from Online Sources.- Exploiting User Feedback to Improve Semantic Web Service Discovery.- A Generic Approach for Large-Scale Ontological Reasoning in the Presence of Access Restrictions to the Ontologys Axioms.- OntoCase-Automatic Ontology Enrichment Based on Ontology Design Patterns.- Graph-Based Ontology Construction from Heterogenous Evidences.- DOGMA: A Disk-Oriented Graph Matching Algorithm for RDF Databases.- Semantically-Aided Business Process Modeling.- Task Oriented Evaluation of Module Extraction Techniques.- A Decomposition-Based Approach to Optimizing Conjunctive Query Answering in OWL DL.- Goal-Directed Module Extraction for Explaining OWL DL Entailments.- Analysis of a Real Online Social Network Using Semantic Web Frameworks.- Coloring RDF Triples to Capture Provenance.- TripleRank: Ranking Semantic Web Data by Tensor Decomposition.- What Four Million Mappings Can Tell You about Two Hundred Ontologies.- Modeling and Query Patterns for Process Retrieval in OWL.- Context and Domain Knowledge Enhanced Entity Spotting in Informal Text.- Using Naming Authority to Rank Data and Ontologies for Web Search.- Executing SPARQL Queries over the Web of Linked Data.- Dynamic Querying of Mass-Storage RDF Data with Rule-Based Entailment Regimes.- Decidable Order-Sorted Logic Programming for Ontologies and Rules with Argument Restructuring.- Semantic Web Service Composition in Social Environments.- XLWrap - Querying and Integrating Arbitrary Spreadsheets with SPARQL.- Optimizing QoS-Aware Semantic Web Service Composition.- Synthesizing Semantic Web Service Compositions with jMosel and Golog.- A Practical Approach for Scalable Conjunctive Query Answering on Acyclic Knowledge Base.- Learning Semantic Query Suggestions.- Investigating the Semantic Gap through Query Log Analysis.- Towards Lightweight and Robust Large Scale Emergent Knowledge Processing.- On Detecting High-Level Changes in RDF/S KBs.- Efficient Query Answering for OWL 2.- Multi Visualization and Dynamic Query for Effective Exploration of Semantic Data.- A Conflict-Based Operator for Mapping Revision.- Functions over RDF Language Elements.- Policy-Aware Content Reuse on the Web.- Exploiting Partial Information in Taxonomy Construction.- Actively Learning Ontology Matching via User Interaction.- Optimizing Web Service Composition While Enforcing Regulations.- A Weighted Approach to Partial Matching for Mobile Reasoning.- Scalable Distributed Reasoning Using MapReduce.- Discovering and Maintaining Links on the Web of Data.- Concept and Role Forgetting in Ontologies.- Parallel Materialization of the Finite RDFS Closure for Hundreds of Millions of Triples.- Semantic Web In Use.- Live Social Semantics.- RAPID: Enabling Scalable Ad-Hoc Analytics on the Semantic Web.- LinkedGeoData: Adding a Spatial Dimension to the Web of Data.- Enrichment and Ranking of the YouTube Tag Space and Integration with the Linked Data Cloud.- Produce and Consume Linked Data with Drupal!.- Extracting Enterprise Vocabularies Using Linked Open Data.- Reasoning about Resources and Hierarchical Tasks Using OWL and SWRL.- Using Hybrid Search and Query for E-discovery Identification.- Bridging the Gap between Linked Data and the Semantic Desktop.- Vocabulary Matching for Book Indexing Suggestion in Linked Libraries - A Prototype Implementation and Evaluation.- Semantic Web Technologies for the Integration of Learning Tools and Context-Aware Educational Services.- Semantic Enhancement for Enterprise Data Management.- Lifting Events in RDF from Interactions with Annotated Web Pages.- A Case Study in Integrating Multiple E-commerce Standards via Semantic Web Technology.- Supporting Multi-view User Ontology to Understand Company Value Chains.- Doctoral Consortium.- EXPRESS: EXPressing REstful Semantic Services Using Domain Ontologies.- A Lexical-Ontological Resource for Consumer Heathcare.- Semantic Web for Search.- Towards Agile Ontology Maintenance.- Ontologies for User Interface Integration.- Semantic Usage Policies for Web Services.- Ontology-Driven Generalization of Cartographic Representations by Aggregation and Dimensional Collapse.- Invited Talks.- Populating the Semantic Web by Macro-reading Internet Text.- Search 3.0: Present, Personal, Precise.

The Semantic Web - ISWC 2008

Research Track.- Involving Domain Experts in Authoring OWL Ontologies.- Supporting Collaborative Ontology Development in Protege.- Identifying Potentially Important Concepts and Relations in an Ontology.- RoundTrip Ontology Authoring.- nSPARQL: A Navigational Language for RDF.- An Experimental Comparison of RDF Data Management Approaches in a SPARQL Benchmark Scenario.- Anytime Query Answering in RDF through Evolutionary Algorithms.- The Expressive Power of SPARQL.- Integrating Object-Oriented and Ontological Representations: A Case Study in Java and OWL.- Extracting Semantic Constraint from Description Text for Semantic Web Service Discovery.- Enhancing Semantic Web Services with Inheritance.- Using Semantic Distances for Reasoning with Inconsistent Ontologies.- Statistical Learning for Inductive Query Answering on OWL Ontologies.- Optimization and Evaluation of Reasoning in Probabilistic Description Logic: Towards a Systematic Approach.- Modeling Documents by Combining Semantic Concepts with Unsupervised Statistical Learning.- Comparison between Ontology Distances (Preliminary Results).- Folksonomy-Based Collabulary Learning.- Combining a DL Reasoner and a Rule Engine for Improving Entailment-Based OWL Reasoning.- Improving an RCC-Derived Geospatial Approximation by OWL Axioms.- OWL Datatypes: Design and Implementation.- Laconic and Precise Justifications in OWL.- Learning Concept Mappings from Instance Similarity.- Instanced-Based Mapping between Thesauri and Folksonomies.- Collecting Community-Based Mappings in an Ontology Repository.- Algebras of Ontology Alignment Relations.- Scalable Grounded Conjunctive Query Evaluation over Large and Expressive Knowledge Bases.- A Kernel Revision Operator for Terminologies - Algorithms and Evaluation.- Description Logic Reasoning with Decision Diagrams.- RDF123: From Spreadsheets to RDF.- Evaluating Long-Term Use of the Gnowsis Semantic Desktop for PIM.- Bringing the IPTC News Architecture into the Semantic Web.- RDFS Reasoning and Query Answering on Top of DHTs.- An Interface-Based Ontology Modularization Framework for Knowledge Encapsulation.- On the Semantics of Trust and Caching in the Semantic Web.- Semantic Web Service Choreography: Contracting and Enactment.- Formal Model for Semantic-Driven Service Execution.- Efficient Semantic Web Service Discovery in Centralized and P2P Environments.- Exploring Semantic Social Networks Using Virtual Reality.- Semantic Grounding of Tag Relatedness in Social Bookmarking Systems.- Semantic Modelling of User Interests Based on Cross-Folksonomy Analysis.- ELP: Tractable Rules for OWL 2.- Term Dependence on the Semantic Web.- Semantic Relatedness Measure Using Object Properties in an Ontology.- Semantic Web in Use Track.- Thesaurus-Based Search in Large Heterogeneous Collections.- Deploying Semantic Web Technologies for Work Integrated Learning in Industry - A Comparison: SME vs. Large Sized Company.- Creating and Using Organisational Semantic Webs in Large Networked Organisations.- An Architecture for Semantic Navigation and Reasoning with Patient Data - Experiences of the Health-e-Child Project.- Requirements Analysis Tool: A Tool for Automatically Analyzing Software Requirements Documents.- OntoNaviERP: Ontology-Supported Navigation in ERP Software Documentation.- Market Blended Insight: Modeling Propensity to Buy with the Semantic Web.- DogOnt - Ontology Modeling for Intelligent Domotic Environments.- Introducing IYOUIT.- A Semantic Data Grid for Satellite Mission Quality Analysis.- A Process Catalog for Workflow Generation.- Inference Web in Action: Lightweight Use of the Proof Markup Language.- Supporting Ontology-Based Dynamic Property and Classification in WebSphere Metadata Server.- Towards a Multimedia Content Marketplace Implementation Based on Triplespaces.- Doctoral Consortium Track.- Semantic Enrichment of Folksonomy Tagspaces.- Contracting and Copyright Issues for Composite Semantic Services.- Parallel Computation Techniques for Ontology Reasoning.- Towards Semantic Mapping for Casual Web Users.- Interactive Exploration of Heterogeneous Cultural Heritage Collections.- End-User Assisted Ontology Evolution in Uncertain Domains.- Learning Methods in Multi-grained Query Answering.

GATE: an Architecture for Development of Robust HLT applications

In this paper we present GATE, a framework and graphical development environment which enables users to develop and deploy language engineering components and resources in a robust fashion. The GATE architecture has enabled us not only to develop a number of successful applications for various language processing tasks (such as Information Extraction), but also to build and annotate corpora and carry out evaluations on the applications generated. The framework can be used to develop applications and resources in multiple languages, based on its thorough Unicode support.

Evolving GATE to meet new challenges in language engineering

In this paper we present recent work on GATE, a widely-used framework and graphical development environment for creating and deploying Language Engineering components and resources in a robust fashion. The GATE architecture has facilitated the development of a number of successful applications for various language processing tasks (such as Information Extraction, dialogue and summarisation), the building and annotation of corpora and the quantitative evaluations of LE applications. The focus of this paper is on recent developments in response to new challenges in Language Engineering: Semantic Web, integration with Information Retrieval and data mining, and the need for machine learning support.

Analysis of named entity recognition and linking for tweets

Applying natural language processing for mining and intelligent information access to tweets (a form of microblog) is a challenging, emerging research area. Unlike carefully authored news text and other longer content, tweets pose a number of new challenges, due to their short, noisy, context-dependent, and dynamic nature. Information extraction from tweets is typically performed in a pipeline, comprising consecutive stages of language identification, tokenisation, part-of-speech tagging, named entity recognition and entity disambiguation (e.g. with respect to DBpedia). In this work, we describe a new Twitter entity disambiguation dataset, and conduct an empirical analysis of named entity recognition and disambiguation, investigating how robust a number of state-of-the-art systems are on such noisy texts, what the main sources of error are, and which problems should be further investigated to improve the state of the art.

Ontology-based information extraction for business intelligence

Business Intelligence (BI) requires the acquisition and aggregation of key pieces of knowledge from multiple sources in order to provide valuable information to customers or feed statistical BI models and tools. The massive amount of information available to business analysts makes information extraction and other natural language processing tools key enablers for the acquisition and use of that semantic information. We describe the application of ontology-based extraction and merging in the context of a practical e-business application for the EU MUSING Project where the goal is to gather international company intelligence and country/region information. The results of our experiments so far are very promising and we are now in the process of building a complete end-to-end solution.

Architectural elements of language engineering robustness

We discuss robustness in LE systems from the perspective of engineering, and the predictability of both outputs and construction process that this entails. We present an architectural system that contributes to engineering robustness and low-overhead systems development (GATE, a General Architecture for Text Engineering). To verify our ideas we present results from the development of a multi-purpose cross-genre Named Entity recognition system. This system aims be robust across diverse input types, and to reduce the need for costly and timeconsuming adaptation of systems to new applications, with its capability to process texts from widely differing domains and genres.

Automatic detection of political opinions in tweets

In this paper, we discuss a variety of issues related to opinion mining from microposts, and the challenges they impose on an NLP system, along with an example application we have developed to determine political leanings from a set of pre-election tweets. While there are a number of sentiment analysis tools available which summarise positive, negative and neutral tweets about a given keyword or topic, these tools generally produce poor results, and operate in a fairly simplistic way, using only the presence of certain positive and negative adjectives as indicators, or simple learning techniques which do not work well on short microposts. On the other hand, intelligent tools which work well on movie and customer reviews cannot be used on microposts due to their brevity and lack of context. Our methods make use of a variety of sophisticated NLP techniques in order to extract more meaningful and higher quality opinions, and incorporate extra-linguistic contextual information.

Microblog-genre noise and impact on semantic annotation accuracy

Using semantic technologies for mining and intelligent information access to microblogs is a challenging, emerging research area. Unlike carefully authored news text and other longer content, tweets pose a number of new challenges, due to their short, noisy, context-dependent, and dynamic nature. Semantic annotation of tweets is typically performed in a pipeline, comprising successive stages of language identification, tokenisation, part-of-speech tagging, named entity recognition and entity disambiguation (e.g. with respect to DBpedia). Consequently, errors are cumulative, and earlier-stage problems can severely reduce the performance of final stages. This paper presents a characterisation of genre-specific problems at each semantic annotation stage and the impact on subsequent stages. Critically, we evaluate impact on two high-level semantic annotation tasks: named entity detection and disambiguation. Our results demonstrate the importance of making approaches specific to the genre, and indicate a diminishing returns effect that reduces the effectiveness of complex text normalisation.

Identifying terms by their family and friends

Multi-word terms are traditionally identified using statistical techniques or, more recently, using hybrid techniques combining statistics with shallow linguistic information. Approaches to word sense disambiguation and machine translation have taken advantage of contextual information in a more meaningful way, but terminology has rarely followed suit. We present an approach to term recognition which identifies salient parts of the context and measures their strength of association to relevant candidate terms. The resulting list of ranked terms is shown to improve on that produced by traditional methods, in terms of precision and distribution, while the information acquired in the process can also be used for a variety of other applications, such as disambiguation, lexical tuning and term clustering.