scholarly journals PNEPs, NEPs for Context Free Parsing: Application to Natural Language Processing

2009 ◽  
pp. 472-479
Author(s):  
Alfonso Ortega ◽  
Emilio del Rosal ◽  
Diana Pérez ◽  
Robert Mercaş ◽  
Alexander Perekrestenko ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Context Free

scholarly journals CYK Parsing over Distributed Representations

Algorithms ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 262
Author(s):  
Fabio Massimo Zanzotto ◽  
Giorgio Satta ◽  
Giordano Cristini
Keyword(s):  
Neural Networks ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Matrix Multiplication ◽  
General Context ◽  
Distributed Representations ◽  
Syntactic Pattern ◽  
Definition Of ◽  
Context Free

Parsing is a key task in computer science, with applications in compilers, natural language processing, syntactic pattern matching, and formal language theory. With the recent development of deep learning techniques, several artificial intelligence applications, especially in natural language processing, have combined traditional parsing methods with neural networks to drive the search in the parsing space, resulting in hybrid architectures using both symbolic and distributed representations. In this article, we show that existing symbolic parsing algorithms for context-free languages can cross the border and be entirely formulated over distributed representations. To this end, we introduce a version of the traditional Cocke–Younger–Kasami (CYK) algorithm, called distributed (D)-CYK, which is entirely defined over distributed representations. D-CYK uses matrix multiplication on real number matrices of a size independent of the length of the input string. These operations are compatible with recurrent neural networks. Preliminary experiments show that D-CYK approximates the original CYK algorithm. By showing that CYK can be entirely performed on distributed representations, we open the way to the definition of recurrent layer neural networks that can process general context-free languages.

scholarly journals Towards a Context-Free Machine Universal Grammar (CF-MUG) in Natural Language Processing

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 165111-165129
Author(s):  
Quanyi Hu ◽  
Jie Yang ◽  
Peng Qin ◽  
Simon Fong
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Universal Grammar ◽  
Free Machine ◽  
Context Free

Researching on Parsing

2013 ◽  
Vol 846-847 ◽  
pp. 1376-1379
Author(s):  
Li Fei Geng ◽  
Hong Lian Li
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Linguistic Analysis ◽  
Syntactic Analysis ◽  
The Core ◽  
Core Technology ◽  
Context Free ◽  
Probabilistic Context ◽  
Context Free Grammars

Syntactic analysis is the core technology of natural language processing and it is the cornerstone for further linguistic analysis. This paper, first introduces the basic grammatical system and summary the technology of current parsing. Then analysis the characteristics of probabilistic context-free grammars deep and introduce the method of improving for probabilistic context-free. The last we point the difficulty of Chinese parsing.

scholarly journals Pemanfaatan Bahasa Alami Dalam Penelusuran Informasi Skripsi Melalui Digital Library

2020 ◽  
Vol 2 (1) ◽  
pp. 22-31
Author(s):  
Dewi Soyusiawaty ◽  
Anna Hendri Soleliza Jones
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Digital Library ◽  
Information Search ◽  
Context Free Grammar ◽  
Flexible System ◽  
Search Form ◽  
Natural Language Interface ◽  
Context Free

Daftar judul skripsi yang ada di web digilib.uad.ac.id belum digunakan secara optimal. Kesulitan menentukan topik serta pengelolaan data pada sistem yang belum memadai menjadi beberapa kendala mahasiswa. Penelitian ini bertujuan membangun pencarian informasi skripsi dengan antarmuka bahasa alami agar mudah dalam menulis kriteria pencarian tanpa harus terikat formulir pencarian. Penelitian ini menggunakan data skripsi untuk dikelola. Pengambilan data dilakukan menggunakan pendekatan Natural Language Processing. Masukan dalam bentuk kalimat bahasa alami digunakan untuk mencari data.  Proses Parsing dilakukan untuk memecah kalimat input dan mendeteksi kata kunci yang relevan. Pengembangan aturan produksi dalam Context Free Grammar diperlukan untuk menerjemahkan bahasa alami ke dalam query.  Kalimat yang melewati tahap parser diterjemahkan ke dalam bahasa SQL. Sistem ini berhasil menampilkan informasi skripsi berupa daftar judul berdasarkan topik, metode, dan objek penelitian sesuai kalimat pencarian dengan nilai precision sebesar 89,3% dan recall sebesar 100%. Keberadaan model pencarian informasi dengan antarmuka bahasa alami dapat menjadi alternatif dalam proses pencarian informasi skripsi guna menyediakan sistem yang lebih fleksibel.  The use of the existing digital library has not been used optimally. Difficulties in determining topics and managing data in an inadequate system are among the obstacles for students. This study aims to build a thesis information search with a natural language interface so that it is easy to write search criteria without having to be tied to a search form. This research uses thesis data to be managed. Data were collected using the Natural Language Processing approach. Input in the form of natural language sentences is used to find data. The parsing process is carried out to break down the input sentence and detect relevant keywords. Development of production rules in Context Free Grammar is necessary to translate natural language into queries. Sentences that go through the parser stage are translated into SQL language. This system succeeds in displaying thesis information in the form of a list of titles based on topics, methods, and research objects according to the search sentence with a precision value of 89% and a recall of 100%. The existence of an information retrieval model with a natural language interface can be an alternative in the thesis information search process in order to provide a more flexible system.

A Review and evaluation of Machine Translation methods for Lumasaaba

2020 ◽  
pp. 3-17
Author(s):  
Peter Nabende
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Machine Translation ◽  
Language Processing ◽  
Research Area ◽  
Data Driven ◽  
East African ◽  
Data Set ◽  
African Languages ◽  
Translation Methods

Natural Language Processing for under-resourced languages is now a mainstream research area. However, there are limited studies on Natural Language Processing applications for many indigenous East African languages. As a contribution to covering the current gap of knowledge, this paper focuses on evaluating the application of well-established machine translation methods for one heavily under-resourced indigenous East African language called Lumasaaba. Specifically, we review the most common machine translation methods in the context of Lumasaaba including both rule-based and data-driven methods. Then we apply a state of the art data-driven machine translation method to learn models for automating translation between Lumasaaba and English using a very limited data set of parallel sentences. Automatic evaluation results show that a transformer-based Neural Machine Translation model architecture leads to consistently better BLEU scores than the recurrent neural network-based models. Moreover, the automatically generated translations can be comprehended to a reasonable extent and are usually associated with the source language input.

1243-P: Novel Use of Natural Language Processing to Identify Reasons for Insulin Discontinuation in Patients with T2DM: A Real-World Evidence Study

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1243-P
Author(s):  
JIANMIN WU ◽  
FRITHA J. MORRISON ◽  
ZHENXIANG ZHAO ◽  
XUANYAO HE ◽  
MARIA SHUBINA ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Real World ◽  
Real World Evidence
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