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In the recruitment domain, knowing the employer industry of jobs is important to get an insight about the demand in each industry. The existing system at CareerBuilder uses an employer name normalization system and an employer knowledge base to infer the employer industry of a job. However, errors may occur during the computation of the job employer and in the construction of the employer knowledge...
The proliferation of Web 2.0 technologies and the increasing use of computer-mediated communication resulted in a new form of written text, termed microtext. This poses new challenges to natural language processing tools which are usually designed for well-written text. This paper proposes a phonetic-based framework for normalizing microtext to plain English and, hence, improve the classification...
Geospatial Intelligence analysis involves the combination of multi-source information expressed in logical form (as sentences or statements), computational form (as numerical models of physics or other processes), and sensor data (as measurements from transducers). Each of these forms has its own way to describe uncertainty or error: e.g., frequency models, algorithmic truncation, floating point roundoff,...
We investigate methods to define a probabilistic logic and their application to multi-source fusion problems in geospatial decision support systems1. We begin with a discussion of augmenting propositional calculus with probabilities. Given a set of sentences, S, each with a known probability, the problem is to determine the probability of a query sentence that is a disjunction of literals appearing...
Obesity has been linked to several types of cancer. Access to adequate health information activates people's participation in managing their own health, which ultimately improves their health outcomes. Nevertheless, the existing online information about the relationship between obesity and cancer is heterogeneous and poorly organized. A formal knowledge representation can help better organize and...
We propose a novel, semantic-reasoning-based approach to look for potentially adverse drug-drug interactions (DDIs) by using a knowledge-base of biomedical public ontologies and datasets in a semantic graph representation. This approach makes it possible to find previously unknown relations between different biological entities like drugs, proteins and biological processes, and perform inferences...
This paper presents a system architecture that designs a querying refinement method. The method employs the general principles of facet analysis in a particular paradigm, as well as the notion of ‘focus’, which is a sort of context for a user query. The method provides the user with contextual information about the query, which is computed by using the user documents provided that the documents are...
Advancement of next generation sequencing and high-throughput technologies has resulted in generation of multi-level of ‘OMICS’ data for many organisms. However, these data are often individually scattered across different repositories based on data type, making it difficult to integrate them. We have addressed this issue through our in-house developed Soybean Knowledge Base [1,2] (SoyKB) framework,...
This paper presents detailed anomaly detection evaluation on operational time-series data of Internet of Things (IoT) based household devices in general and Heating, Ventilation and Air Conditioning (HVAC) systems in specific. Due to the number of issues observed during evaluation of widely used distance-based, statistical-based, and cluster-based anomaly detection techniques, we also present a pattern-based...
Semantic similarity of texts is one of the important areas of Natural Language Processing, and there are several approaches to measure similarity: statistical, WordNet based, and hybrid. For all of these approaches, a lexical knowledge is used such as corpus or semantic network. WordNet is one of the most preferred and mature lexical knowledge base. In this study, we have focused on measuring semantic...
In article is considered the approach to use of original elements of conceptual graphs notations at the complex description of declarative and procedural components of the control expert systems (ES) within the general problems of design automation of the chosen ES class.
A multi-objective particle swarm algorithm based on the active learning (MOPSAL) approach is proposed that combines a Multi-Objective particle swarm optimization (MOPSO) with an Pareto Active Learning (PAL) approach. In MOPSAL, the candidate solution set is produced by a sampling method based on mutation operator and preselected by the PAL approach. Then, the best Pareto solution from the candidate...
From investigating graphical passwords (NGPs), we define set-labellings and set-colorings (set-labelling/colorings) of networks/graphs, and define the new edge-colorings called adjacent 1-common edge-coloring and vertex 1-common edge-coloring. Some connections between traditional graph colorings and our set-labelling/colorings are found. Conversely, our results can be used to design more complicated...
A large software project usually has lots of various textual learning resources about its API, such as tutorials, mailing lists, user forums, etc. Text retrieval technology allows developers to search these API learning resources for related documents using free-text queries, but it suffers from the lexical gap between search queries and documents. In this paper, we propose a novel approach for improving...
Psoriasis is a chronic, recurrent, inflammatory skin disease, with varied incidence rates for various populations in different regions of the world. According to statistics, the prevalence of psoriasis in European countries is about 1% ∼ 3%, and 0.47% for China in 2008, which appears on the rise year by year. [1,2] Evidence suggests that genetic and environmental factors play important roles in the...
In recent years, people pay more and more attention to the knowledge of health care and longevity. As an important branch of the Traditional Chinese Medicine (TCM), health preservation is a subject for studying the theories and methods to prevent diseases and to maintain personal health. We aim to provide the general public as well as the TCM practitioners and students with a convenient way to access...
Data interoperability is a prerequisite to achieve cross-community and cross-application sharing of information and knowledge. Heterogeneous data from multiple sources including semantic and non-semantic data sources (e.g. SNS data, web data, relational data, RDF, XML, CSV, etc.) have an important effect for IoT service provisioning. The data are not in a same type or format always that requires to...
The traditional monolithic hospital focused healthcare system organically developed to address acute conditions. In recent years, healthcare needs have shifted from treating acute conditions to meeting an unprecedented chronic disease burden. Chronic disease healthcare is based on continued delivery outside healthcare facilities, deep understanding of individual health state, managing individualized...
The expert selection is an important decision problem in the research and development process of complex product systems (CoPS) projects and suitable experts will facilitate the successful task achievement. Existing methods for the expert selection are mostly based on the individual performance, whereas the task characteristics of CoPS projects and the knowledge correlationship between candidates...
One of the fundamental means for interaction and coordination between humans and cognitive robots is knowledge sharing in general and formal concept comprehension in particular. A cognitive knowledge base (CKB) is introduced as a formal structure of collective knowledge embodied by a weighted hierarchical concept network. This paper formally describes a CKB based on concept algebra and semantic algebra...
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