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Bardia Rafieian, Pedro Hermosilla and Pere-Pau Vázquez
In data science and visualization, dimensionality reduction techniques have been extensively employed for exploring large datasets. These techniques involve the transformation of high-dimensional data into reduced versions, typically in 2D, with the aim ...
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Lukas Busch, Ruben van Heusden and Maarten Marx
Page stream segmentation (PSS) is the task of retrieving the boundaries that separate source documents given a consecutive stream of documents (for example, sequentially scanned PDF files). The task has recently gained more interest as a result of the di...
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Benjamin Shade and Eduardo G. Altmann
Quantifying the dissimilarity of two texts is an important aspect of a number of natural language processing tasks, including semantic information retrieval, topic classification, and document clustering. In this paper, we compared the properties and per...
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Eduardo Cibrián, Jose María Álvarez-Rodríguez, Roy Mendieta and Juan Llorens
The use of different techniques and tools is a common practice to cover all stages in the development life-cycle of systems generating a significant number of work products. These artefacts are frequently encoded using diverse formats, and often require ...
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Su Yang and Farzin Deravi
In this paper, a novel re-engineering mechanism for the generation of word embeddings is proposed for document-level sentiment analysis. Current approaches to sentiment analysis often integrate feature engineering with classification, without optimizing ...
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Joaquin Gómez and Pere-Pau Vázquez
The comparison of documents?such as articles or patents search, bibliography recommendations systems, visualization of document collections, etc.?has a wide range of applications in several fields. One of the key tasks that such problems have in common i...
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Andrey Bogdanchikov, Dauren Ayazbayev and Iraklis Varlamis
The rapid development of natural language processing and deep learning techniques has boosted the performance of related algorithms in several linguistic and text mining tasks. Consequently, applications such as opinion mining, fake news detection or doc...
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Min-Hsien Weng, Shaoqun Wu and Mark Dyer
With the rapidly growing number of scientific publications, researchers face an increasing challenge of discovering the current research topics and methodologies in a scientific domain. This paper describes an unsupervised topic detection approach that u...
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Peter Bajcsy, Nicholas J. Schaub and Michael Majurski
This paper addresses the problem of designing trojan detectors in neural networks (NNs) using interactive simulations. Trojans in NNs are defined as triggers in inputs that cause misclassification of such inputs into a class (or classes) unintended by th...
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Kuekyeng Kim, Yuna Hur, Gyeongmin Kim and Heuiseok Lim
In an age overflowing with information, the task of converting unstructured data into structured data are a vital task of great need. Currently, most relation extraction modules are more focused on the extraction of local mention-level relations?usually ...
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