15 research outputs found
Extending pythonQA with knowledge from stackOverflow
Question and Answering (QA) Systems provide a platform where users can ask questions in natural language to a system and get answers retrieved from a knowledge base. The work proposed in PythonQA create a Question and Answer System for the Python Programming Language. The knowledge is built from the Python Frequent Answered Questions (PyFAQ). In this paper, we extend the PythonQA system by enhancing the Knowledge Base with Question-Answer pairs from the StackExchange Python Question Answering Community Site. Some tests were performed to analyze the impact of a richer Knowledge Base on the PythonQA system, increasing the number of answer candidates.info:eu-repo/semantics/publishedVersio
Ferramenta para monitoramento de redes wireless com foco em amenizar a aglomeração de usuário em pontos de acesso.
By monitoring the network, you can improve the quality of service in order to increase efficiency and productivity. This work describes a tool developed called CTIWifi, which used PHP libraries together with information collections from the network, the tool that aims to assist in wireless network monitoring, presenting easy-to-read graphics of infrastructure information.O monitoramento da rede, pode-se melhorar a qualidade do servic¸o, tendo em vista aumentar a eficiencia e produtividade. Este trabalho descreve ˆ uma ferramenta desenvolvida denominada CTIWifi, a qual utilizado bibliotecas PHP junto com coletas de informac¸oes da rede, a ferramenta que tem como ˜ objetivo auxiliar no monitoramento da rede sem fio apresentando graficos de ´ facil leitura das informac¸ ´ oes da infraestrutura
Development of Q&A systems using AcQA
In order to help the user to search for relevant information, Question and Answering (Q&A) Systems
provide the possibility to formulate the question freely in a natural language, retrieving the most
appropriate and concise answers. These systems interpret the user question to understand his
information needs and return him the more adequate replies in a semantic sense; they do not perform
a statistical word search like happens in the existing search engines. There are several approaches to
developing and deploying Q&A Systems, making it hard to choose the best way to build the system.
To turn easier this process, we are proposing a way to automatically create Q&A Systems (AcQA)
based on DSLs, thus allowing the setup and the validation of the Q&A System independent of the
implementation techniques. With our proposal (AcQA language), we want the developers to focus
on the data and contents, instead of implementation details. We conducted an experiment to assess
the feasibility of using AcQA. The study was carried out with people from the computer science field
and shows that our language simplifies the development of a Q&A System.info:eu-repo/semantics/publishedVersio
Topic maps constraint languages : understanding and comparing
Topic map constraint language (TMCL) provides a means to express constraints on topic maps conforming to ISO/IEC 13250. In this article, we will use a test suite and show, step-by-step, the way we handled several kinds of topic maps constraints in many different instances in order to answer questions like: Do they do the same job? Are there some kinds of topic maps constraints that are easier to specify with one of them? Do you need different background to use the tools? Is it possible to use them in similar situations (the same topic maps instances)? May we use them to produce an equal result? How do AsTMa!, OSL, Toma and XTche relate to TMCL? What kind of constraints each one of these three cannot specify? We will conclude this paper with a summary of the comparisons accomplished between those topic maps constraint languages over the use case proposed.(undefined
Topic maps constraint languages: understanding and comparing
Topic Map Constraint Language (TMCL) provides a means
to express constraints on topic maps conforming to ISO/IEC 13250. In
this article, we will use a test suite and show, step-by-step, the way we
handled several kinds of Topic Maps constraints in many d
Topic maps constraint specification languages : comparing AsTMa!, OSL, and XTche
Topic maps are an ISO standard for the representation and interchange of knowledge, with an emphasis on the findability
of information. A topic map can represent information using topics (representing any concept), associations (which
represent the relationships between them), and occurrences (which represent relationships between topics and
information resources relevant to them). They are thus similar to semantic networks and both concept and mind maps in
many respects. According to Topic Map Data Model (TMDM), Topic Maps are abstract structures that can
encode knowledge and connect this encoded knowledge to relevant information resources.
In order to cope with a broad range of scenarios, a topic is a very wide concept. On one hand, this makes Topic Maps a
convenient model for knowledge representation; but on the other hand, this can also put in risk the topic map
consistency. A set of semantic constraints must be imposed to the topic map in order to grant its consistency.
Currently, we can find three approaches to constrain Topic Maps -- AsTMa!, OSL, and
XTche -- that allow us to specify constraints and to validate the instances of a family of
topic maps against that set of rules. With these resemblances it is easy to conclude that they are quite similar.
However they differ in some fundamental concepts. These three Topic Maps constraint specification languages were hardly
tested and benchmarked with a huge test suite. The most significant results will be discussed in this paper.
In this article, we will use that test suite and show, step-by-step, the way we handled several kinds of Topic Maps
constraints in many different instances in order to answer questions like: Do they do the same job? Are there some kind
of Topic Maps constraints that are easier to specify with one of them? Do you need different background to use the
tools? Is it possible to use them in similar situations (the same topic maps instances)? May we use them to produce an
equal result? How do AsTMa!, OSL, and XTche relate to Topic Maps Constraint Language (TMCL)? What kind of constraints
each one of these three can not specify?
What is the intersection area of these three? What kind of constraints each one of these three is able to specify?
We will conclude this paper with a summary of the comparisons accomplished between those Topic Maps constraint
languages over the use case proposed
Navegando na rede semântica dos topic maps com o Ulisses
A norma ISO-IEC 13250 Topic Maps, composta principalmente
de tópicos interligados através de associações, define uma rede
semântica estruturada sobre um sistema de informação, criando uma
ponte entre a gestão de informação e os domínios de representação de
conhecimento. A estrutura de dados que um topic map representa é um
grafo; portanto, uma das melhores maneiras de visualizar um grafo é
percebendo sua estrutura de vértices (tópicos) e arestas (associações).
Assim sendo, este artigo tem por objetivo a visualização eficiente desta
camada semântica através de navegadores Web, permitindo que todos os
vértices (tópicos) do grafo topic map sejam acessados em uma navegação
conceitual, seja por ligações HTML (links), seja navegando no próprio
grafo visualmente. Para apresentar essa abordagem de navegação em
Topic Maps, divide-se o artigo em 3 partes: primeiro, apresentam-se os
conceitos básicos de Topic Maps, para então, descrever algumas técnicas
de sua visualização. Por fim, descrever-se-á a ferramenta de visualização
desenvolvida, caracterizando as técnicas empregadas em seu desenvolvimento
Comparing topic maps constraint specification languages
Topic Map Constraint Language (TMCL) provides a means to express constraints on topic maps conforming to ISO/IEC 13250. In this article, we will use a test suite and show, step-by-step, the way we handled several kinds of Topic Maps constraints in many different instances in order to answer questions like: Do they do the same job? Are there some kinds of Topic Maps constraints that are easier to specify with one of them? Do you need different background to use the tools? Is it possible to use them in similar situations (the same topic maps instances)? May we use them to produce an equal result? How do AsTMa!, OSL, Toma, and XTche relate to Topic Maps Constraint Language (TMCL)? What kind of constraints each one of these three can not specify? We will conclude this paper with a summary of the comparisons accomplished between those Topic Maps constraint languages over the use case proposed
Implementing TMCL: XTche : a topic map schema and constraint specification language
In this paper we present a Topic Maps Validation System – XTche constraint language and its processor. We started
with our strong motivation to check a topic map for syntactic and semantic correctness – as a notation to describe an
ontology that supports a sophisticated computer system where its validation is crucial!
Then we assume XTM and TMCL as starting points and we used our background in compilers and XML validation to
come up with our proposal. XTche complies with all requirements stated for TMCL but it is an XML Schema oriented
language. This idea brings two benefits: on one hand it allows for the syntactic specification of Topic Maps (not only
the constraints), eliminating the need for two separated specifications (schema and constraints); and on the other hand
it enables the use of an XML Schema editor (like XMLSpy) to provide a graphical interface and the basic syntactic
checker.
With XTche,atopicmapdesignerdefinesasetofrestrictionsthatguaranteethataparticulartopicmapissemanticallyvalid
Network traffic analysis - a different approach using incoming and outgoing traffic differences
The network traffic analysis is a fundamental area on network management because the network anomalies may affect the network quality of service. However, the data network traffic anomalies are still a critical issue. On last years signal processing methods like wavelet-based ones have been used to detect anomalies on network traffic, specially because wavelet transforms allow the selection of signal characteristics via a combined time-frequency representation. This paper explores a simple and fast wavelet
transform for analyzing the network flow, considering the difference between incoming and outgoing traffic data, for improving identification of deny of service attacks