نتایج جستجو برای: automatic testing
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The proliferation of misleading information in everyday access media outlets such as social media feeds, news blogs, and online newspapers have made it challenging to identify trustworthy news sources, thus increasing the need for computational tools able to provide insights into the reliability of online content. In this paper, we focus on the automatic identification of fake content in online...
An interactive information retrieval system that provides different types of summaries of retrieved documents according to each user’s information needs can be effective for understanding the contents. The purpose of this study is to build a multi-document summarizer to produce summaries according to such viewpoints. As an exploratory stage of investigation, we examined the effectiveness of gen...
The Unified Astronomy Thesaurus (UAT) is an open, interoperable and community-supported thesaurus which unifies the existing divergent and isolated Astronomy & Astrophysics vocabularies into a single high-quality, freely-available open thesaurus formalizing astronomical concepts and their inter-relationships. The UAT builds upon the existing IAU Thesaurus with major contributions from the astro...
Model transformation can’t be directly tested using program techniques. Those have to be adapted to model characteristics. In this paper we focus on one test technique: mutation analysis. This technique aims to qualify a test data set by analyzing the execution results of intentionally faulty program versions. If the degree of qualification is not satisfactory, the test data set has to be impro...
Extractive summarization is the strategy of concatenating extracts taken from a corpus into a summary, while abstractive summarization involves paraphrasing the corpus using novel sentences. We define a novel measure of corpus controversiality of opinions contained in evaluative text, and report the results of a user study comparing extractive and NLG-based abstractive summarization at differen...
We have developed a summarization system, TAS (Technical Article Summarizer), which, when provided with a patient record and journal articles returned by a search, automatically generates a summary that is tailored to the patient characteristics. We hypothesize that a personalized summary will allow a physician to more quickly find information relevant to patient care. In this paper, we present...
The authors have developed the Internet browser application Gymn@zilla for L2-learning. In this paper they present a dynamical image annotation: Gymn@zilla automatically provides explanatory images drawn from Internet for words in L2. The Internet-images are often photos of daily events. The authors discuss the psycholinguistic implications of images in L2 learning in general and specifically t...
A closed-loop feedback control model of the Software Test Process (STP) is described. The model is grounded in the well established theory of Automatic Control. It offers a formal and novel procedure for using product reliability or failure intensity as a basis for closed loop control of the STP. The reliability or the failure intensity of the product is compared against the desired reliability...
Multi-dimensional latent text models, such as factorial LDA (f-LDA), capture multiple factors of corpora, creating structured output for researchers to better understand the contents of a corpus. We consider such models for clinical research of new recreational drugs and trends, an important application for mining current information for healthcare workers. We use a “three-dimensional” f-LDA va...
We are conducting research on multi-document summarization, participating in a competition of sum-marization, TSC (Text Summarization Challenge) task organized by NTCIR-3 project. In a dry run, we conceived a new extraction method for multi-document summarization which extracts a set of sentences that maximizes coverage of an original text and minimizes redundancy of a summary. Thinking over th...
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