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Big Data and Cognitive Computing, Volume 3, Issue 2

June 2019 - 15 articles

Cover Story: Word embeddings have been successful in many natural language processing tasks, although they characterize the meaning of a word by uninterpretable “context signatures”. Such a representation can render the results obtained using embeddings as difficult to interpret. Neighboring word vectors may have similar meanings, but in what way are they similar? That similarity may represent a synonymy, metonymy, or even antonymy relation. In the cognitive psychology literature, in contrast, concepts are frequently represented by their relations with properties. These properties are produced by test subjects when asked to describe the important features of concepts. As such, they form a natural, intuitive feature space. In this work, we present a neural network-based method for mapping a distributional semantic space onto a human-built property space automatically. View this paper.
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Articles (15)

  • Article
  • Open Access
2 Citations
7,927 Views
12 Pages

In a human society with emergent technology, the destructive actions of some pose a danger to the survival of all of humankind, increasing the need to maintain peace by overcoming universal conflicts. However, human society has not yet achieved compl...

  • Article
  • Open Access
5,018 Views
12 Pages

The fundamental challenge of salient object detection is to find the decision boundary that separates the salient object from the background. Low-rank recovery models address this challenge by decomposing an image or image feature-based matrix into a...

  • Article
  • Open Access
5 Citations
5,932 Views
20 Pages

Weakly-Supervised Image Semantic Segmentation Based on Superpixel Region Merging

  • Quanchun Jiang,
  • Olamide Timothy Tawose,
  • Songwen Pei,
  • Xiaodong Chen,
  • Linhua Jiang,
  • Jiayao Wang and
  • Dongfang Zhao

In this paper, we propose a semantic segmentation method based on superpixel region merging and convolutional neural network (CNN), referred to as regional merging neural network (RMNN). Image annotation has always been an important role in weakly-su...

  • Review
  • Open Access
143 Citations
59,303 Views
30 Pages

Big data and business analytics are trends that are positively impacting the business world. Past researches show that data generated in the modern world is huge and growing exponentially. These include structured and unstructured data that flood org...

  • Article
  • Open Access
8 Citations
6,267 Views
11 Pages

Word embeddings have been very successful in many natural language processing tasks, but they characterize the meaning of a word/concept by uninterpretable “context signatures”. Such a representation can render results obtained using embe...

  • Article
  • Open Access
10 Citations
6,086 Views
14 Pages

Cognitive deterioration caused by illness or aging often occurs before symptoms arise, and its timely diagnosis is crucial to reducing its medical, personal, and societal impacts. Brain–computer interfaces (BCIs) stimulate and analyze key cereb...

  • Article
  • Open Access
76 Citations
10,397 Views
22 Pages

Understanding the corrosion risk of a pipeline is vital for maintaining health, safety and the environment. This study implemented a data-driven machine learning approach that relied on Principal Component Analysis (PCA), Particle Swarm Optimization...

  • Article
  • Open Access
156 Citations
14,734 Views
18 Pages

Automatic Human Brain Tumor Detection in MRI Image Using Template-Based K Means and Improved Fuzzy C Means Clustering Algorithm

  • Md Shahariar Alam,
  • Md Mahbubur Rahman,
  • Mohammad Amazad Hossain,
  • Md Khairul Islam,
  • Kazi Mowdud Ahmed,
  • Khandaker Takdir Ahmed,
  • Bikash Chandra Singh and
  • Md Sipon Miah

In recent decades, human brain tumor detection has become one of the most challenging issues in medical science. In this paper, we propose a model that includes the template-based K means and improved fuzzy C means (TKFCM) algorithm for detecting hum...

  • Communication
  • Open Access
60 Citations
12,744 Views
10 Pages

The Emerging Role of Blockchain Technology Applications in Routine Disease Surveillance Systems to Strengthen Global Health Security

  • Vijay Kumar Chattu,
  • Anjali Nanda,
  • Soosanna Kumary Chattu,
  • Syed Manzoor Kadri and
  • Andy W Knight

Blockchain technology has an enormous scope to revamp the healthcare system in many ways as it improves the quality of healthcare by data sharing among all the participants, selective privacy and ensuring data safety. This paper explores the basics o...

  • Article
  • Open Access
41 Citations
14,617 Views
17 Pages

This essay argues that a new subfield of AI governance should be explored that examines the policy-making process and its implications for AI governance. A growing number of researchers have begun working on the question of how to mitigate the catast...

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Big Data Cogn. Comput. - ISSN 2504-2289Creative Common CC BY license