Merging and ranking answers in the semantic web:the wisdom of crowds

In this paper we propose algorithms for combining and ranking answers from distributed heterogeneous data sources in the context of a multi-ontology Question Answering task. Our proposal includes a merging algorithm that aggregates, combines and filters ontology-based search results and three different ranking algorithms that sort the final answers according to different criteria such as popularity, confidence and semantic interpretation of results. An experimental evaluation on a large scale corpus indicates improvements in the quality of the search results with respect to a scenario where the merging and ranking algorithms were not applied. These collective methods for merging and ranking allow to answer questions that are distributed across ontologies, while at the same time, they can filter irrelevant answers, fuse similar answers together, and elicit the most accurate answer(s) to a question.

Overcoming schema heterogeneity between linked semantic repositories to improve coreference resolution

Schema heterogeneity issues often represent an obstacle for discovering coreference links between individuals in semantic data repositories. In this paper we present an approach, which performs ontology schema matching in order to improve instance coreference resolution performance. A novel feature of the approach is its use of existing instance-level coreference links defined in third-party repositories as background knowledge for schema matching techniques. In our tests of this approach we obtained encouraging results, in particular, a substantial increase in recall in comparison with existing sets of coreference links.

Semantic search meets the Web

While semantic search technologies have been proven to work well in specific domains, they still have to confront two main challenges to scale up to the Web in its entirety. In this work we address this issue with a novel semantic search system that a) provides the user with the capability to query Semantic Web information using natural language, by means of an ontology-based Question Answering (QA) system [14] and b) complements the specific answers retrieved during the QA process with a ranked list of documents from the Web [3]. Our results show that ontology-based semantic search capabilities can be used to complement and enhance keyword search technologies.

A framework for evaluating semantic metadata

Because poor quality semantic metadata can destroy the effectiveness of semantic web technology by hampering applications from producing accurate results, it is important to have frameworks that support their evaluation. However, there is no such framework developedto date. In this context, we proposed i) an evaluation reference model, SemRef, which sketches some fundamental principles for evaluating semantic metadata, and ii) an evaluation framework, SemEval, which provides a set of instruments to support the detection of quality problems and the collection of quality metrics for these problems. A preliminary case study of SemEval shows encouraging results.

An infrastructure for semantic web portals

This paper presents our Semantic Web portal infrastructure, which focuses on how to enhance knowledge access in traditional Web portals by gathering and exploiting semantic metadata. Special attention is paid to three important issues that affect the performance of knowledge access: i) high quality metadata acquisition, which concerns how to ensure high quality while gathering semantic metadata from heterogeneous data sources; ii) semantic search, which addresses how to meet the information querying needs of ordinary end users who are not necessarily familiar with the problem domain or the supported query language; and iii) semantic browsing, which concerns how to help users understand and explore the problem domain.

AquaLog : an ontology-driven question answering system for organizational semantic intranets

The semantic web vision is one in which rich, ontology-based semantic markup will become widely available. The availability of semantic markup on the web opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system which takes queries expressed in natural language and an ontology as input, and returns answers drawn from one or more knowledge bases (KBs). We say that AquaLog is portable because the configuration time required to customize the system for a particular ontology is negligible. AquaLog presents an elegant solution in which different strategies are combined together in a novel way. It makes use of the GATE NLP platform, string metric algorithms, WordNet and a novel ontology-based relation similarity service to make sense of user queries with respect to the target KB. Moreover it also includes a learning component, which ensures that the performance of the system improves over the time, in response to the particular community jargon used by end users.

The usability of semantic search tools:a review

The goal of semantic search is to improve on traditional search methods by exploiting the semantic metadata. In this paper, we argue that supporting iterative and exploratory search modes is important to the usability of all search systems. We also identify the types of semantic queries the users need to make, the issues concerning the search environment and the problems that are intrinsic to semantic search in particular. We then review the four modes of user interaction in existing semantic search systems, namely keyword-based, form-based, view-based and natural language-based systems. Future development should focus on multimodal search systems, which exploit the advantages of more than one mode of interaction, and on developing the search systems that can search heterogeneous semantic metadata on the open semantic Web.

An infrastructure for acquiring high quality semantic metadata

Because metadata that underlies semantic web applications is gathered from distributed and heterogeneous data sources, it is important to ensure its quality (i.e., reduce duplicates, spelling errors, ambiguities). However, current infrastructures that acquire and integrate semantic data have only marginally addressed the issue of metadata quality. In this paper we present our metadata acquisition infrastructure, ASDI, which pays special attention to ensuring that high quality metadata is derived. Central to the architecture of ASDI is a verification engine that relies on several semantic web tools to check the quality of the derived data. We tested our prototype in the context of building a semantic web portal for our lab, KMi. An experimental evaluation comparing the automatically extracted data against manual annotations indicates that the verification engine enhances the quality of the extracted semantic metadata.

PowerAqua:fishing the semantic web

The Semantic Web (SW) offers an opportunity to develop novel, sophisticated forms of question answering (QA). Specifically, the availability of distributed semantic markup on a large scale opens the way to QA systems which can make use of such semantic information to provide precise, formally derived answers to questions. At the same time the distributed, heterogeneous, large-scale nature of the semantic information introduces significant challenges. In this paper we describe the design of a QA system, PowerAqua, designed to exploit semantic markup on the web to provide answers to questions posed in natural language. PowerAqua does not assume that the user has any prior information about the semantic resources. The system takes as input a natural language query, translates it into a set of logical queries, which are then answered by consulting and aggregating information derived from multiple heterogeneous semantic sources.

Semantic search components:a blueprint for effective query language interfaces

Formulating complex queries is hard, especially when users cannot understand all the data structures of multiple complex knowledge bases. We see a gap between simplistic but user friendly tools and formal query languages. Building on an example comparison search, we propose an approach in which reusable search components take an intermediary role between the user interface and formal query languages.

SemSearch:a search engine for the semantic web

Existing semantic search tools have been primarily designed to enhance the performance of traditional search technologies but with little support for ordinary end users who are not necessarily familiar with domain specific semantic data, ontologies, or SQL-like query languages. This paper presents SemSearch, a search engine, which pays special attention to this issue by providing several means to hide the complexity of semantic search from end users and thus make it easy to use and effective.

Semantic annotation for knowledge management:requirements and a survey of the state of the art

While much of a company's knowledge can be found in text repositories, current content management systems have limited capabilities for structuring and interpreting documents. In the emerging Semantic Web, search, interpretation and aggregation can be addressed by ontology-based semantic mark-up. In this paper, we examine semantic annotation, identify a number of requirements, and review the current generation of semantic annotation systems. This analysis shows that, while there is still some way to go before semantic annotation tools will be able to address fully all the knowledge management needs, research in the area is active and making good progress.

AquaLog : an ontology-driven question answering system to interface the semantic web

The semantic web (SW) vision is one in which rich, ontology-based semantic markup will become widely available. The availability of semantic markup on the web opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system which takes queries expressed in natural language (NL) and an ontology as input, and returns answers drawn from one or more knowledge bases (KB). AquaLog presents an elegant solution in which different strategies are combined together in a novel way. AquaLog novel ontology-based relation similarity service makes sense of user queries.

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 lighten the burden of its creation. After having described some particularities of this kind of knowledge, we introduce ClaimSpotter, our approach to support its ‘capture’, based on the elicitation of a number of recommendations which are presented for consideration to our annotators (or analysts), and give some elements of evaluation.

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.