Showing all 15 Tech Reports linked to Victoria Uren

State of the art on Semantic Question Answering

We analyze the contributions, challenges and dimensions of question answering on the Semantic Web by looking at the state of the art on semantic question answering systems, and the implications in traditional methods on ontology selection, mapping and semantic similarity measures to balance the heterogeneity and large scale semantic data with run time performanceread more

ID: kmi-07-03

Date: 2007

Author(s): Vanessa Lopez, Enrico Motta, Victoria Uren, Marta Sabou

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SemSearch: A Search Engine for the Semantic Web

Semantic search promises to produce precise answers to user queries by taking advantage of the availability of explicit semantics of information in the context of the semantic web. Existing tools have been primarily designed to enhance the performance of traditional search technologies but with little support for naive users, i.e., ordinary end users who are not necessarily familiar with domain specific semantic data, ontologies, or SQL-like query languages. This paper presents SemSearch, a...read more

ID: kmi-06-11

Date: 2006

Author(s): Yuangui Lei, Victoria Uren, Enrico Motta

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LRD: Latent Relation Discovery for Vector Space Expansion and Information Retrieval

In this paper, we propose a text mining method called LRD (latent relation discovery), which extends the traditional vector space model of document representation in order to improve information retrieval (IR) on documents and document clustering. Our LRD method extracts terms and entities, such as person, organization, or project names, and discovers relationships between them by taking into account their co-occurrence in textual corpora. Given a target entity, LRD discovers other entities...read more

ID: kmi-06-09

Date: 2006

Author(s): Alexandre Gonçalves, Jianhan Zhu, Dawei Song, Victoria Uren, Roberto Pacheco

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Extracting Domain Ontologies with CORDER

The CORDER web mining engine developed at the Knowledge Media Institute computes a lexical coocurrence network out of websites - a binary relation R. A natural extension of CORDER would be that of learning an ontology. However, our work shows that coocurrence proves insufficient to discover concepts and conceptual taxonomies (i.e. very simple ontologies) out of this network. To tackle this problem two unsupervised learning methods were studied based, on the one hand, on set similarity (and thus...read more

ID: kmi-05-14

Date: 2005

Author(s): Camilo Thorne, Jianhan Zhu, Victoria Uren

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Sensemaking Tools for Understanding Research Literatures: Design, Implementation and User Evaluation

This paper describes the work undertaken in the Scholarly Ontologies Project. The aim of the project has been to develop a computational approach to support scholarly sensemaking, through interpretation and argumentation, enabling researchers to make claims: to describe and debate their view of a document's key contributions and relationships to the literature. The project has investigated the technicalities and practicalities of capturing conceptual relations, within and between conventional...read more

ID: kmi-05-09

Date: 2005

Author(s): Victoria Uren, Simon Buckingham Shum, Michelle Bachler, Gangmin Li

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Experiences of Two Task Driven User Studies of Hypermedia Information Systems

We present two small scale user studies of hypermedia information systems: a hypermedia discourse system designed as an environment for researchers to summarize and share key ideas from research papers as a claim network, and a web browser plug-in which annotates terms related to a selected ontology on the fly. The first study investigated whether a claim network created by one user could help others learn about a domain. The second study investigated whether information extraction techniques...read more

ID: kmi-05-04

Date: 2005

Author(s): Victoria Uren, Philipp Cimiano, Simon Buckingham Shum, Enrico Motta

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Adaptive Named Entity Recognition for Social Network Analysis and Domain Ontology Maintenance

We present a system which unearths relationships between named entities from information in Web pages. We use an adaptive named entity recognition system, ESpotter, which recognizes entities of various types with high precision and recall from various domains on the Web, to generate entity data such as peoples' names. Given an entity, we apply a link analysis algorithm to the entity data for finding other entities which are closely related to it. We present our results to people whose names had...read more

ID: kmi-04-30

Date: 2004

Author(s): Jianhan Zhu, Alexandre L. Goncalves, Victoria Uren

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Modelling Naturalistic Argumentation in Research Literatures: Representation and Interaction Design Issues

This paper characterises key weaknesses in the ability of current digital libraries to support scholarly inquiry, and as a way to address these, proposes computational services grounded in semiformal models of the naturalistic argumentation commonly found in research lteratures. It is argued that a design priority is to balance formal expressiveness with usability, making it critical to co-evolve the modelling scheme with appropriate user interfaces for argument construction and analysis. We...read more

ID: kmi-04-28

Date: 2004

Author(s): Simon J. Buckingham Shum, Victoria Uren, Gangmin Li, Bertrand Sereno, Clara Mancini

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ESpotter: Adaptive Named Entity Recognition for Web Browsing

Web users are facing information overload problems, i.e., it is hard for them to find desired information on the web. Hence the growing interest in named entity recognition (NER) for discovering relevant information on users behalf. We present a browser plug-in called ESpotter which adapts lexicons and patterns to a domain hierarchy consisting of domains on the web and user preferences for accurate and efficient NER. Mappings are created from domain independent types to domain...read more

ID: kmi-04-12

Date: 2004

Author(s): Jianhan Zhu, Victoria Uren, Enrico Motta

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Nootropia: a Self-Organising Agent for Adaptive Document Filtering

This paper presents Nootropia, a self-organising information agent, capable of evaluating documents according to a user's multiple and changing interests. In Nootropia, a hierarchical term network that takes into account term dependencies is used to represent a user's multiple topics of interest. Non-linear document evaluation is established on that network based on a directed spreading activation model. We then introduce a process for adjusting the network in response to changes in user...read more

ID: kmi-04-02

Date: 2004

Author(s): Nikolaos Nanas, Victoria Uren, Anne de Roeck, John Domingue

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Semantic Annotation Support in the Absence of Consensus

We are interested in the annotation of knowledge which does not necessarily require a consensus. Scholarly debate is an example of such a category of knowledge where disagreement and contest are widespread and desirable, and unlike many Semantic Web approaches, we are interested in the capture and the compilation of these conflicting viewpoints and perspectives. The Scholarly Ontologies project provides the underlying formalism to represent this meta-knowledge, and we will look at ways to...read more

ID: kmi-04-01

Date: 2004

Author(s): Bertrand Sereno, Victoria Uren, Simon Buckingham Shum, Enrico Motta

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Interfaces for Capturing Interpretations of Research Literature

The ClaiMaker collaborative sense-making and annotation tools allow single users and groups to build and query hypertextual argument maps of research literatures. We describe the discourse ontology used by the system, and four design principles that were followed to make it usable for non-knowledge engineers. We present several generations of capture interfaces showing how they are evolving to make ClaiMaker more accessible for novice users.read more

ID: kmi-03-06

Date: 2003

Author(s): Victoria Uren, Bertrand Sereno, Simon Buckingham Shum, Gangmin Li

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A Comparative Study of Term Weighting Methods for Information Filtering

The users of an information filtering system can only be expected to provide a small amount of information to initialize their user profile. Therefore, term weighting methods for information filtering have somewhat different requirements to those for information retrieval and text categorization. We present a comparative evaluation of term weighting methods, including one novel method, relative document frequency, designed specifically for information filtering. The best weighting methods...read more

ID: kmi-03-04

Date: 2003

Author(s): Nikolaos Nanas, Victoria Uren, Anne De Roeck

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Scholarly Publishing and Argument in Hyperspace

The World Wide Web is opening up access to documents and data for scholars. However it has not yet impacted on one of the primary activities in research: assessing new findings in the light of current knowledge and debating it with colleagues. The ClaiMaker system uses a directed graph model with similarities to hypertext, in which new ideas are published as nodes, which other contributors can build on or challenge in a variety of ways by linking to them. Nodes and links have semantic structure...read more

ID: kmi-03-03

Date: 2003

Author(s): Victoria Uren, Simon Buckingham Shum, Gangmin Li, John Domingue, Enrico Motta

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ClaiMaker:Weaving a Semantic Web of Research Papers

The usability of research papers on the Web would be enhanced by a system that explicitly modelled the rhetorical relations between claims in related papers. We describe ClaiMaker, a system for modelling readers' interpretations of the core content of papers. ClaiMaker provides tools to build a Semantic Web representation of the claims in research papers using an ontology of relations. We demonstrate how the system can be used to make inter-document queries.read more

ID: kmi-03-02

Date: 2003

Author(s): Gangmin Li, Victoria Uren, Enrico Motta, Simon Buckingham Shum, John Domingue

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Jobs

Research Assistant / Associate

Knowledge Media Institute (KMi)
£29,799 - £38,833
Based in Milton Keynes
Temporary contract until 31st December 2018

The Open University’s Knowledge Media Institute (KMi) is a distinct research unit within the Faculty of Science, Technology, Engineering and Mathematics (STEM). KMi is looking for a Research Assistant or a Research Associate to work on an EU funded project – Hub4NGI. The project will strengthen and coordinate the work done by ongoing and upcoming projects, focusing on Next Generation Internet Experimentation (NGI-E), with the goal to transform the current NGI-E setting into an increasingly...

Project Officer - Data Hub Development

Knowledge Media Institute (KMi)
�32,548 - �38,833
Based in Milton Keynes
Temporary contract until 30 June 2019

The Open University�s Knowledge Media Institute (KMi) is a distinct research unit within the Faculty of Science, Technology, Engineering and Mathematics (STEM). KMi is looking for a Project Officer to support the maintenance and evolution of the MK Data Hub, a computational infrastructure for acquiring and managing city data originally developed in the context of the MK:Smart project, www.mksmart.org. The position is supported by two projects funded by the European Regional Development...

Web Developer (Front-end and CMS)

Knowledge Media Institute (KMi)
£26,495 - £31,604
Based in Milton Keynes
Temporary contract until 30 June 2018

The Knowledge Media Institute (KMi) is a distinct research unit within the Faculty of Science, Technology, Engineering and Mathematics (STEM) at the Open University. KMI is looking for a Web Developer to join their team of developers and researchers that runs a large aggregator of research papers called CORE, and a set of projects promoting principles of Open Science. CORE provides free access to the full-texts of 8 million+ Open Access research papers as well as a number of information...

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