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Using semantic techniques, we determined a probabilistic score indicating whether news stories were more optimistic (or solutions-oriented), versus their being more pessimistic (or threnodic). We observed over the length of our study that some news outlets, which were comparable in their topical coverage, quantity of output, and geographical focus, differed vastly in their level of optimistic or solutions-oriented...
We present work on using a domain model to guide text interpretation, in the context of a project that aims to interpret English questions as a sequence of queries to be answered from structured databases. We adapt a broad-coverage and ambiguity-enabled natural language processing (NLP) system to produce domain-specific logical forms, using knowledge of the domain to zero in on the appropriate interpretation...
Existing approaches for selecting the most appropriate reasoner for different semantic applications mainly relies on discussions between application developers and reasoner experts. However this approach will become inadequate with the increasing adoption of Semantic Web technologies in applications from different domains and the rapid development of OWL reasoning technologies. This work proposes...
Consumption of business processes provided in form of Web sites have become a part of our daily life for attending our personal and business needs. In order to obtain the best solution for a particular task, users often combine several Web sites. However, currently the composition of Web sites, coordination of the execution of such Web sites compositions is done completely manually. In this paper,...
Web APIs, characterized by their relative simplicity and their natural suitability for the Web, have become increasingly dominant in the world of services on the Web. Despite their popularity, Web APIs are so heterogeneous in terms of the underlying principles adopted and the means used for publishing them that discovering, understanding and notably invoking Web APIs is nowadays more an art than a...
Web service discovery is the process of finding web service providers that satisfy specific service requester requirements. In real life scenarios, services are often described with complex constraints and contain dynamic aspects that are not adequately supported by most of the current discovery systems. In this paper, we propose a novel OWL-S based semantic service discovery system for dynamically...
In the relation extraction of semantic relations, it is not uncommon to face settings in which the training data provides very few instances of some relation classes. This is mostly due to the high cost of producing such data and to the class imbalance problem, which may result in some classes presenting small frequencies even with a large annotated corpus. This work thus presents a semi-supervised...
Recognizing new and emerging events in a stream of news documents requires understanding the semantic structure of news reported in natural language. New event detection (NED) is the task of recognizing when a news document discusses a completely novel event. To be successful at this task, we argue a NED method must extract and represent the type of event and its participants as well as the temporal...
The paper addresses some roles of concept-based representations in document clustering to support knowledge discovery. Computational Intelligence algorithms can benefit from semantic networks in the definition of similarity between pairs of documents. After analyzing the tuning of semantic networks in a systematic fashion, the research defines and evaluates a novel semantic-based metrics, which integrates...
Geographic feature categorization from text addresses the need for querying and finding geographic features from text documents. Although many text classification techniques have been developed, there are limitations to apply to geographic features due to the uniqueness of the geography features. In this paper we propose a method to classify geographic features based on latent semantic analysis and...
Our research addresses the question as to whether automatically collected quantitative data about people's behavior online can be analyzed to spot patterns that indicate behaviors of interest. Based on ethnographic studies, we find that people, going about their routine work, exhibit patterns in terms of their routine online activities and work rhythms. Such patterns can be comprised of many diverse...
One of the promises of the Semantic Web is to support applications that easily and seamlessly deal with heterogeneous data. Most data on the Web, however, is in the Extensible Markup Language (XML) format, but using XML requires applications to understand the format of each data source that they access. To achieve the benefits of the Semantic Web involves transforming XML into the Semantic Web language,...
One central task to the idea of Semantic Web is reasoning over semantic descriptions of web pages and information items available on the Web. A flagship project that is advancing the state of the art in reasoning with Web scale data is the Large Knowledge Collider (LarKC). Having a plug gable architecture, LarKC enables the interested users to test their reasoning approaches with very little overhead...
Emerging semantic search techniques require fast comparison of large "concept trees". This paper addresses the challenges involved in fast computation of similarity between two large concept trees using a CUDA-enabled GPGPU co-processor. We propose efficient techniques for the same using fast hash computations, membership tests using Bloom Filters and parallel reduction. We show how a CUDA-enabled...
Provenance is becoming an important issue as a reliable estimator of data quality. However, provenance collection mechanisms in the reservoir engineering domain often result in missing provenance information. In this paper, we address the problem of predicting missing provenance information in reservoir engineering. Based on the observation that data items with specific semantic "connections"...
Data quality is a critical problem for the Semantic Web. We propose that the degree to which a triple deviates from similar triples can be an important heuristic for identifying errors. Inspired by data dependency, which has shown promise in database data quality research, we introduce Semantic Dependency to assess quality of Semantic Web data. The system first builds a summary graph for finding candidate...
We present a natural-language question-answering system that gives access to the accumulated knowledge of one of the largest community projects on the Web â" Wikipedia â" via an automatically acquired structured knowledge base. Key to building such a system is to establish mappings from natural language expressions to semantic representations. We propose to acquire these mappings by data-driven...
We are interested in the problem of discourse parsing of textual documents. We present a novel end-to-end discourse parser that, given a plain text document in input, identifies the discourse relations in the text, assigns them a semantic label and detects discourse arguments spans. The parsing architecture is based on a cascade of decisions supported by Conditional Random Fields (CRF). We train and...
In this paper, we address the task of semantic service retrieval based on natural language queries. We analyze identifiers of services, operations, and parameters extracted from WSDL service descriptions with respect to their semantic content. In order to measure the semantic similarity between query and service description, we introduce a novel computationally efficient document similarity measure...
We illustrate an architecture for a conversational agent based on a modular knowledge representation. This solution provides intelligent conversational agents with a dynamic and flexible behavior. The modularity of the architecture allows a concurrent and synergic use of different techniques, making it possible to use the most adequate methodology for the management of a specific characteristic of...
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