In the domain of medical, biomedical ontologies play an important role for extracting the information and knowledge about the specific domain and present the problem in more understandable form. Now a day there are a ...
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ISBN:
(纸本)9781728116648
In the domain of medical, biomedical ontologies play an important role for extracting the information and knowledge about the specific domain and present the problem in more understandable form. Now a day there are a lot of work in done in this field. Also, many evaluation techniques are made to check the correctness or quality of the ontologies. In this paper we proposed an evaluation technique that use the structure characteristics to examine the quality of ontologies. For this we select anatomy domain ontology and apply the proposed evaluation criteria. In our evaluation criteria, we check the quality of ontology on the basis of structured characteristics and compare the results of all ontologies and chose the best one.
In this paper we present a methodology for introducing customizable metalogic features in logic-basedknowledge representation and reasoning languages. The proposed approach is based on concepts of introspection and r...
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Answer extraction is the core technology of question answering (QA) system. Most of the previous works were based on syntactic features and knowledge base, which highly required the language knowledge. Accordingly, we...
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As the DoD and Military acquisitions shift the paradigm from antiquated software capabilities to artificial intelligence (AI) and machine learning (ML) capabilities, they need to ensure key infrastructure (big data an...
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ISBN:
(数字)9783030234072
ISBN:
(纸本)9783030234072;9783030234065
As the DoD and Military acquisitions shift the paradigm from antiquated software capabilities to artificial intelligence (AI) and machine learning (ML) capabilities, they need to ensure key infrastructure (big data and knowledge artifacts) is also mature enough to handle the transition. Before any organizations or domains develop or adopt a strategy based on AI, ML, or any other form of intelligent system, they need to do a self-assessment that answers three key questions. How well does your organization/domain share knowledge? What is the state of your data? Do you understand the cognitive requirements? Answering and understanding these questions is the key to knowing where you are now (point A) so you can take actionable and progressive steps towards where you want to go (point B) to make your organization or domain AI-capable. To provide the answers and/or a path to solving the questions above we execute a Mission engineering (ME) process that analyzes the organization's or domain's state of readiness. The ME process is a detailed analysis that provides an assessment of how the people, systems, knowledge, data, and processes are aligned to the operational outcomes. ME adds a layer of operational viability to existing engineering processes with the goal of ensuring the program enhances knowledge sharing, reduces cognitive burdens, and increases semantic understanding.
The paper suggests analysis of multicore neuroprocessing structures based on co-design of hardware and software. The development of the task is achieved by using of set-theoretic analyses of all internal algorithms wi...
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The paper proposes a method for solving problems of classifying multi-step attacks on wireless sensor networks in the conditions of uncertainty (incompleteness and inconsistency) of the observed signs of attacks. The ...
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ISBN:
(数字)9781728157610
ISBN:
(纸本)9781728157627
The paper proposes a method for solving problems of classifying multi-step attacks on wireless sensor networks in the conditions of uncertainty (incompleteness and inconsistency) of the observed signs of attacks. The method aims to eliminate the uncertainty of classification of attacks on networks of this class one the base of the use of neural network approaches to the processing of incomplete and contradictory knowledge on possible attack characteristics. It allows increasing objectivity (accuracy and reliability) of information security monitoring in modern software and hardware systems and Internet of Things networks that actively exploit advantages of wireless sensor networks.
The problem that we address here is given n job seekers and n job offers, where each job seeker has ranked all job offers in order of preference given by a suitability function, and vice versa;the goal is to compute t...
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ISBN:
(纸本)9781450371797
The problem that we address here is given n job seekers and n job offers, where each job seeker has ranked all job offers in order of preference given by a suitability function, and vice versa;the goal is to compute the minimum set of skills to be offered to the job seekers, so that a) a global stable marriage between job seekers and potential employers can be reached, and b) the degree of satisfaction for that stable marriage might be maximum. To achieve this goal, we have designed an iterative algorithmic solution that can be solved in polynomial time. Additionally, we illustrate our solution with an use case based on a numerical example.
The small inter-class variance and the large intra-class variance make the few-shot and fine-grained image classification more difficult because the machine cannot obtain enough information from only a few images. The...
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ISBN:
(数字)9781728113319
ISBN:
(纸本)9781728113326
The small inter-class variance and the large intra-class variance make the few-shot and fine-grained image classification more difficult because the machine cannot obtain enough information from only a few images. The external knowledge contains more semantics and can support the model to extract important features, while most of existing few-shot learning algorithms only focus on leveraging the visual features from images, little attention has been paid to the cross-modal external knowledge. In this paper, we propose a knowledge-based fine-grained classification mechanism for few-shot learning, which can overcome the difficulty of only obtaining limited and discriminative features from unimodal samples. We extract the visual features and the knowledge features from textual descriptions and a domain-specific knowledge graph at global and local levels to build the semantic space. To tackle the gap between multimodal features, we propose a mirror framework, named Mirror Mapping Network (MMN), to map the multimodal features into the same semantic space with two directions. Extensive experimental results show that our method outperforms the state-of-the-art.
The generalization and systematization of various scientific views of both domestic and foreign researchers on the problem of educational data mining (EDM) and their application to support decision-making on the educa...
ISBN:
(数字)9781728148106
ISBN:
(纸本)9781728148113
The generalization and systematization of various scientific views of both domestic and foreign researchers on the problem of educational data mining (EDM) and their application to support decision-making on the educational process management. Particular attention is paid to the problems of automatic extraction of interpreted knowledge from educational data in order to transfer it to users and facilitate the processes of interactive computing and communication among users. The proposed methods and models allow increasing the effectiveness of decision-making process at all stages of the educational process management. The novelty of the work results is a new approach to the extraction of interpretable knowledgebased on the use of a special class of neural network models, as well as the hybridization of several approaches developed as part of data mining into a single learning environment in order to implement an end-to-end learning strategy, including the steps of data collecting and analyzing, knowledge extracting and management. The paper presents the fragments of the developed software that provides EDM by individual methods.
Artificial intelligence and Machine learning advancements in stimulation of human knowledge to computers has led to the softwarebased application / program called chatbot. A chatbot acts as a conventional agent which...
Artificial intelligence and Machine learning advancements in stimulation of human knowledge to computers has led to the softwarebased application / program called chatbot. A chatbot acts as a conventional agent which uses natural languages for communicating with operators. The chatbots are aware of self learning algorithms, for example natural language processing (NLP). These software programs are made to help people and have a one-on-one interaction with them (either in text or speech format). The proposed chatbot provides a platform for crime registration and also getting information about various types of crimes. We can find chatbots in the field of entertainment, query clarification, social media, e-commerce sites etc. but rarely can we find chatbots serving the purpose of security and crime related functions. Our proposed system collects various information from the victims so that the authorities could cross-verify the information provided. It gives a stage for people to report about the crimes, getting data about different sorts of violations. It gathers different check archives from the casualties so the specialists could cross-confirm the data given. The chatbot works on the principle of natural language processing algorithm.
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