Named entity recognition is a basic problem in natural language processing, and also an indispensable part of many natural language processing technologies such as information extraction and information retrieval. There are a large number of proprietary ...

Word embeddings are very useful in variety of natural language processing tasks. Recently, more researches have focused on learning word embeddings with morphological knowledge of words, such as character and subword information. In this paper, we ...

DBSCAN algorithm is a density-based clustering algorithm, which is widely used in various fields and can identify clusters of arbitrary shape. Aiming at the existing problems that the selection of neighborhood radius parameter Eps depends on manual ...

Nowadays, Neural sequence-to-sequence models have become the common approach for abstractive text summarization. In this way, the abstract is closer to the natural language, not just the excerpt and recomposition of the original text. However, these ...

Indian English (IE) derives from British English, but they differ in many aspects. It varies from speech to word, and is a typical variety of English. At present, it is hard to see researches on continuous speech recognition (CSR) of lesser-known ...

Twitter is a popular microblogging platform that provides a tremendous amount of data, which can be used for sentiment analysis. Accordingly, numerous existing studies have concentrated on social media and sentiment analysis. The current study presents ...

In this paper, we present a deep learning based approach to assign POS tags to words in a piece of text given to it as input. We propose an unsupervised approach owing to the lack of a large Sanskrit annotated corpora and use the untagged Sanskrit ...

Table-to-text generation involves using natural language to describe a table which has formal structure and valuable information. Open-domain table-to-text especially refers to table-to-text generation for open domain. This paper introduces a theme ...

Sentence classification, which is the foundation of the subsequent text-based processing, plays an important role in the intelligent question answering (IQA). Convolutional neural networks (CNN) as a kind of common architecture of deep learning, has been ...

We propose a novel approach to generate aspect hierarchies that proved to be consistently correct compared with human-generated hierarchies. We present an unsupervised technique using Rhetorical Structure Theory and graph analysis. We evaluated our ...

The sentiment analysis of film reviews is the basis for obtaining the opinions of the audience, and has a very important influence on the movie public opinion control and the stimulation of potential consumers. This paper focuses on the short-text movie ...

We have implemented a highway-LSTM-CRF(Long Short-Term Memory, LSTM for short; Conditional Random Field, CRF for short) model for Chinese NER(Named entity recognition, NER for short), which encodes a sequence of input characters as well as all potential ...

Image caption has been widely studied recently which, likes the human to understand a scene, learns the high-level semantic descriptions for a single image. To achieve this goal, many recent methods divide the task into two stages, namely, the encoder ...

Many methods about face recognition have been put forward. Generally, the feature of the face image is extracted and then the classifier is used to complete the face recognition. There is no direct relationship between the method of feature extracting ...

Binary Neural Networks (BNNs), whose weights and activations can be represented by a single bit, are gaining more and more attention. Because their inference speed and memory consumption are far superior to full-precision neural networks. However, the ...

The traditional Mel Frequency Cepstral Coefficient (MFCC) feature can only reflect low frequency information, ignoring high frequency signals. In order to solve this problem, this paper uses the Mel frequency decomposition to decompose the speech signal ...

Neuroimaging in the context of brain disease is becoming more and more important. Brain detection and segmentation are two fundamental steps in neuroimage analysis. Because the cost of manual segmentation of the brain is too much, more and more ...

Face fusion, which have widely applied in various of applications, has been receiving much attention. At present, the main face fusion method based on facial feature point matching is adopted, which rely on a large number of feature engineering based on ...

Most of the current information retrieval are based on keyword information appearing in the text or statistical information according to the number of vocabulary words. It is also possible to add additional semantic information by using synonyms, ...

Blood transfusion is generally significant for the human life and it is required in the case of surgery and medical emergencies. The blood assignment problem was introduced to improve the management of available blood in stock in order to minimize ...