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In this paper, we propose a dictionary screening method for embedding compression in text classification tasks. The key purpose of this method is to evaluate the importance of each keyword in the dictionary. To this end, we first train a…

Computation and Language · Computer Science 2022-11-24 Jing Zhou , Xinru Jing , Muyu Liu , Hansheng Wang

We present three innovations in tokenization and subword segmentation. First, we propose to use unsupervised morphological analysis with Morfessor as pre-tokenization. Second, we present an algebraic method for obtaining subword embeddings…

Computation and Language · Computer Science 2024-10-04 Jindřich Libovický , Jindřich Helcl

The use of complex networks as a modern approach to understanding the world and its dynamics is well-established in literature. The adjacency matrix, which provides a one-to-one representation of a complex network, can also yield several…

Social and Information Networks · Computer Science 2023-01-23 Mariane B. Neiva , Odemir M. Bruno

Large-alphabet strings are common in scenarios such as information retrieval and natural-language processing. The efficient storage and processing of such strings usually introduces several challenges that are not witnessed in…

Data Structures and Algorithms · Computer Science 2024-05-03 Diego Arroyuelo , Gabriel Carmona , Héctor Larrañaga , Francisco Riveros , Carlos Eugenio Rojas-Morales , Erick Sepúlveda

Neural networks, particularly Transformer-based architectures, have achieved significant performance improvements on several retrieval benchmarks. When the items being retrieved are documents, the time and memory cost of employing…

Information Retrieval · Computer Science 2020-05-12 Sebastian Hofstätter , Hamed Zamani , Bhaskar Mitra , Nick Craswell , Allan Hanbury

Taxonomies have been widely used in various machine learning and text mining systems to organize knowledge and facilitate downstream tasks. One critical challenge is that, as data and business scope grow in real applications, existing…

Computation and Language · Computer Science 2021-04-13 Xiangchen Song , Jiaming Shen , Jieyu Zhang , Jiawei Han

Text summarization can be classified into two approaches: extraction and abstraction. This paper focuses on extraction approach. The goal of text summarization based on extraction approach is sentence selection. One of the methods to obtain…

Information Retrieval · Computer Science 2009-06-26 Ladda Suanmali , Naomie Salim , Mohammed Salem Binwahlan

In-place associative integer sorting technique was proposed for integer lists which requires only constant amount of additional memory replacing bucket sort, distribution counting sort and address calculation sort family of algorithms. The…

Data Structures and Algorithms · Computer Science 2012-09-18 A. Emre Cetin

In this article, we give a precise mathematical meaning to `linear? time' that matches experimental behaviour of the algorithm. The sorting algorithm is not our own, it is a variant of radix sort with counting sort as a subroutine. The true…

Computational Complexity · Computer Science 2019-01-01 Laurent Lyaudet

Box folding represents a crucial challenge for automated packaging systems. This work bridges the gap between existing methods for folding sequence extraction and approaches focused on the adaptability of automated systems to specific box…

In this paper, we investigate the application of text classification methods to support law professionals. We present several experiments applying machine learning techniques to predict with high accuracy the ruling of the French Supreme…

Computation and Language · Computer Science 2017-10-26 Octavia-Maria Sulea , Marcos Zampieri , Shervin Malmasi , Mihaela Vela , Liviu P. Dinu , Josef van Genabith

We consider the set of finite random words $\mathcal A^\star$, with independent letters drawn from a finite or infinite totally ordered alphabet according to a general probability distribution. On a specific subset of $\mathcal A^\star$,…

Probability · Mathematics 2012-04-22 Elahe Zohoorian Azad

Text clustering holds significant value across various domains due to its ability to identify patterns and group related information. Current approaches which rely heavily on a computed similarity measure between documents are often limited…

Information Retrieval · Computer Science 2025-04-09 Laurence Hirsch , Robin Hirsch , Bayode Ogunleye

This paper introduces a new statistical approach to partitioning text automatically into coherent segments. Our approach enlists both short-range and long-range language models to help it sniff out likely sites of topic changes in text. To…

cmp-lg · Computer Science 2008-02-03 Doug Beeferman , Adam Berger , John Lafferty

This paper presents a versatile technique for the purpose of feature selection and extraction - Class Dependent Features (CDFs). We use CDFs to improve the accuracy of classification and at the same time control computational expense by…

Machine Learning · Computer Science 2014-12-30 Kratarth Goel , Raunaq Vohra , Ainesh Bakshi

Sampling (evenly) the suffixes from the suffix array is an old idea trading the pattern search time for reduced index space. A few years ago Claude et al. showed an alphabet sampling scheme allowing for more efficient pattern searches…

Data Structures and Algorithms · Computer Science 2014-12-04 Szymon Grabowski , Marcin Raniszewski

There have been some works that learn a lexicon together with the corpus to improve the word embeddings. However, they either model the lexicon separately but update the neural networks for both the corpus and the lexicon by the same…

Computation and Language · Computer Science 2017-07-25 Yuanzhi Ke , Masafumi Hagiwara

We solve the problem of finding interspersed maximal repeats using a suffix array construction. As it is well known, all the functionality of suffix trees can be handled by suffix arrays, gaining practicality. Our solution improves the…

Data Structures and Algorithms · Computer Science 2013-04-03 Veronica Becher , Alejandro Deymonnaz , Pablo Ariel Heiber

Text classification stands as a cornerstone within the realm of Natural Language Processing (NLP), particularly when viewed through computer science and engineering. The past decade has seen deep learning revolutionize text classification,…

Computation and Language · Computer Science 2025-04-23 Marco Siino , Ilenia Tinnirello , Marco La Cascia

This paper describes the results of some experiments exploring statistical methods to infer syntactic behavior of words and morphemes from a raw corpus in an unsupervised fashion. It shares certain points in common with Brown et al (1992)…

Computation and Language · Computer Science 2007-05-23 Mikhail Belkin , John Goldsmith
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