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When manually testing Web sites humans can go with vague, yet general instructions, such as "add the product to shopping cart and proceed to checkout". Can we teach a robot to follow such instructions as well?In this paper I present a novel model, called semantic usage patterns which allows us to capture the general topics behind the individual steps of interactions. These models can be...
The application of information retrieval techniques to search tasks in software engineering is made difficult by the lexical gap between search queries, usually expressed in natural language (e.g. English), and retrieved documents, usually expressed in code (e.g. programming languages). This is often the case in bug and feature location, community question answering, or more generally the communication...
Software documentation is a very crucial resource for developers in understanding various aspects of software development process. A unique nature of such documentation is the presence of code elements embedded in natural-language texts that explain their purposes, usages and mutual relations with others. Some recent work has explored that nature for different purposes such as discovering code elements...
The question-answering systems were being investigated for several decades, but the majority of researches were carried out in English. The subject of this paper is the knowledge-based question-answering system. The unique mathematical model describes the process of answering when the question is presented in Russian as a natural language. The model is executed by mapping the question to the existing...
A design pattern describes a general solution to a design problem occurring repeatedly in many systems. Indeed, software designers adapt the pattern solution to their specific applications. Therefore, its design must show the variations points which will be adopted for certain systems. Hence, the expression of the variability when modeling the pattern is crucial. The design pattern is usually modeled...
This paper describes a new kind of knowledge representation and mining system which we are calling the Semantic Knowledge Graph. At its heart, the Semantic Knowledge Graph leverages an inverted index, along with a complementary uninverted index, to represent nodes (terms) and edges (the documents within intersecting postings lists for multiple terms/nodes). This provides a layer of indirection between...
The great part of fuzzy-linguistic research assumes the fuzzy complement as a good candidate for representing the meaning of negation. However, linguistic studies show that both acquisition and use of negation are way more complex than that. After reconsidering a way in which the negation is used in the natural language discourse, this paper focuses on reflecting a use of negation in domains in which...
When a robot is deployed to a new setting, it must reason about how to accomplish the goals of domain-appropriate tasks within the environment it is situated. We investigate the problem of enabling robots to interactively learn how to perform known tasks in new environments. Each task is composed of a sequence of parameterized actions, which we assume are given to the robot in the form of a task recipe...
The large volume of information stored in electronical health records is very valuable in the medical field, e.g., for clinical research and administrative purposes. However, health care professionals still face difficulties to recover and select relevant data. Although literature has investigated the influence of lexical, syntactical and semantic parameters in information retrieval techniques, few...
We present initial findings from an experiment where we used Semantic Free Utterances — vocalizations and sounds without semantic content — as an alternative to Natural Language in a child-robot collaborative game. We tested (i) if two types of Semantic Free Utterances could be accurately recognized by the children; (ii) what effect the type of Semantic Free Utterances had as part of help-giving behaviors...
An approach to summarizing of results from a class of usability studies is presented. It is based on an original theory of modal language grounding. Relevant part of this theory is briefly presented and is further compared to the classical theory of fuzzy linguistic summarization known from data science literature. An example of usability studies is carried out with respect to model in which end users...
An original architecture for production and usage of modal linguistic summaries in IoT contexts and domains is presented. The underlying research takes into account basic features of real IoT contexts and tries to map them effectively into a set of functional requirements. The architecture is strongly influenced and supported by original models of natural language processing, developed interactive...
Based on a framework for English, we developed a Vietnamese Question Answering System. The learning paradigm in the framework reduces the burden of providing supervision during semantic parsing. Whilst taking the advantages from this mechanism, we further create our own feature calculation which is suitable for Vietnamese. A method of dynamic learning for feature computation is also presented in this...
This paper presents a dialog system for the user in interacting with a smart home system. Instead of using just a voice control for appliances, a dialog system gives the user a more natural way of communication with the smart home. The dialog system can take different forms of instruction from the user and provides services to the user. The user can inquire the system about some information instead...
In modern military operations the emphasis is on smaller teams and more ad hoc teamwork. This requires greater agility both in terms of capturing actionable intelligence as well as appropriate dissemination and fusion of that information to coalition team members based on their tasks and need to know. In previous research and development we have explored the potential for a controlled natural language...
Deep learning models can infer complex patterns present in natural language text. Relative to n-gram models, deep learning models can capture more complex statistical patterns based on smaller training corpora. In this paper we explore the use of a particular deep learning model, document vectors (DVs), for feature location. DVs seem well suited to use with source code, because they both capture the...
To facilitate software refactoring, a number of approaches and tools have been proposed to suggest where refactorings should be conducted. However, identification of such refactoring opportunities is usually difficult because it often involves difficult semantic analysis and it is often influenced by many factors besides source code. For example, whether a software entity should be renamed depends...
The rapid growth of the Semantic Web in the last years has led to the emergence of Ontology-Based Question Answering systems, namely systems that exploit the ontological structure of data in order to interpret and answer natural language questions. In this paper, we are interested in question answering scenarios where both semantic data and user questions can be characterized by vagueness and we propose...
Several challenges face the interlinking of large RDF datasets. Perhaps some of the most salient are the polysemy of natural language labels and the lack of reference anchors or starting points. In this paper we propose a novel interlinking method, called TERA, driven by text annotation. The proposed method consists in annotating the same textual context with two different datasets and comparing the...
In this paper, we present the work related to syntactic annotation of Marathi text using Ruled-based approach which is very essential in Sense Disambiguation of a natural language text. We have implemented a system for generating and applying natural language patterns to overcome the sense ambiguity problem. We manipulate the grammatical structure of sentence to give the correct output for Marathi...
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