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Question answering (QA) is the task of automatically answering a question posed in natural language. Its applied to several domains, and it is a specific type of information retrieval, that has three components such as question processing, information retrieval, and answer extraction. By analysing the user question, we intend to improve the precision of Question answering systems by focusing namely...
Piaget's classic work on cognitive development showed that engaging learners in critical discussions with peers about ideas that are different than theirs leads to deep conceptual understanding. Implementing such an approach in computer science and, more generally, STEM, courses has some specific challenges. Based on Piaget's theory, we have developed a highly innovative collaborative learning approach...
Neural language models, such as word embedding, can effectively embed words into vector spaces and preserve linguistic regularities and semantic relationships. However, few researchers have shown their effectiveness on medical terms and relationships. In this paper, we study the applicability of word2vec, a well-known technique for word embedding, to embed medical terms and relations based on different...
The present work describes the Moodle Analytics Dashboard (MAD), a tool developed to allow the visualization of students and professors logs in Moodle disciplines. MAD provides an easy way to obtain graphical visualization of several aspects related to students and professors accesses in virtual learning disciplines, thus helping professors to better follow teaching and learning process, as well as...
GitHub (https://sithub.com/) is a web-based repository for software projects and is reportedly the world's largest open source community, hosting over 31 million repositories that include both code and the documentation for that code. GitHub includes development tools such as issue tracking (bug reports and feature requests), notifications, diffs, and status dashboards; as well as social features...
Many real-world graphs, including those storing various forms of biological data, are of such large size that storing and processing their information has too high a cost. As a result, one possible solution is to compress the graphs by merging nodes into supernodes. This study introduces a genetic algorithm for graph compression that is based on the similarity of nodes, where two nodes are considered...
Named Entity Recognition (NER) plays a significant role in Information Extraction (IE). In English, the NER systems have achieved excellent performance, but for the Indonesian language, the systems still need a lot of improvement. To create a reliable NER system using machine learning approach, a massive dataset to train the classifier is a must. Several studies have proposed methods in automatically...
The ontology matching process with background knowledge is more suitable to match heterogeneous ontologies, since background knowledge is used as a mediator or a reference to identify relation between two concepts being matched. This method is called indirect matching and the system is called indirect matching system. This paper reviews the motivation that described the urgency of ontology matching,...
A co-creation approach to tackling ill-structured problems (ISPs) for tertiary students is proposed. Key findings of a preliminary study assessing the approach's learning effectiveness are discussed. The new approach is more in line with problem solving in the real world and improves cognitive, meta-cognitive, and epistemic cognitive learning.
The innovative brand “The internet of Me” is a recent research area that highlight the prevalence of personalization across the internet and focuses on the user habits and actions tracked from his interaction with the web content. This paradigm presents an efficient way to define the user experience, preferences useful in e-commerce, marketing, social and search purpose. In this paper we are interested...
Enormous efforts of human volunteers have made Wikipedia become a treasure of textual knowledge. Relation extraction that aims at extracting structured knowledge in the unstructured texts in Wikipedia is an appealing but quite challenging problem because it's hard for machines to understand plain texts. Existing methods are not effective enough because they understand relation types in textual level...
This paper addresses the task of assigning multiple labels of fine-grained named entity (NE) types to Wikipedia articles. To address the sparseness of the input feature space, which is salient particularly in fine-grained type classification, we propose to learn article vectors (i.e. entity embeddings) from hypertext structure of Wikipedia using a Skip-gram model and incorporate them into the input...
DBpedia is a huge dataset essentially extracted from the content and structure of Wikipedia. We present a new extraction producing a linked data representation of the editing history of Wikipedia pages. This supports custom querying and combining with other data providing new indicators and insights. We explain the architecture, representation and an immediate application to monitoring events.
Recently, the use of service robots has increased considerably and their social contribution is expected. It is desirable that a robot, as a provider of operational information, can answer questions in both the open domain and intended operations, to respond to questions in a manner that satisfies users. This paper proposes a question answering system that can respond to questions in both intended...
This paper presents a method which detects and tracks objects for navigation of a maritime surface vehicle. The method uses stereo vision system which finds saliency map, calculates disparity and distance from the stereo vision image. The method adopts frequency-tuned saliency map and finds dissimilar area in the image with the template which is found by the salient region detection. It is possible...
Recently, the use of service robots has increased considerably and their social contribution is expected. It is desirable that a robot, as a provider of operational information, can answer questions in both the open domain and intended operations, to respond to questions in a manner that satisfies users. This paper proposes a question answering system that can respond to questions in both intended...
This paper presents an overview of the 5th Competition on Recognition of Online Handwritten Mathematical Expressions (CROHME). As in previous years, the main task is formula recognition from handwritten strokes (Task 1). Additional tasks include classification of isolated symbols (Task 2a), classification of isolated valid and invalid symbols (Task 2b), a new task on parsing formula structure from...
Core periphery structure is a meso-scale property of complex networks. Core periphery structures can help identify the relationships between cohesive core clusters surrounded by sparse peripheries. The knowledge about such relationships can have many practical applications in real world complex networks. For example, in a web based network between all blogs on different topics, peripheries connecting...
In recent years, the amount of entities in large knowledge bases has been increasing rapidly. Such entities can help to bridge unstructured text with structured knowledge and thus be beneficial for many entity-centric applications. The key issue is to link entity mentions in text with entities in knowledge bases, where the main challenge lies in mention ambiguity. Many methods have been proposed to...
This paper analyses two impromptu crowd science movements, comparing the TVTropes wiki community with the Bechdel Wallace test movement. Impromptu crowd science contributors engage in methodical knowledge creation, in absence of academic scientists' involvement. The two examples illustrate the potential of these movements to create data, analyses and concepts relevant for social and humanistic disciplines,...
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