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.

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 Basic challenges in natural language processing systems

2020 ◽  
pp. 41-45
Author(s):  
O. Hyryn
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Information Search ◽  
Question Answering ◽  
Syntactic Analysis ◽  
Anaphora Resolution ◽  
Grammatical Structure ◽  
English Sentence ◽  
Improved Model

The article proceeds from the intended use of parsing for the purposes of automatic information search, question answering, logical conclusions, authorship verification, text authenticity verification, grammar check, natural language synthesis and other related tasks, such as ungrammatical speech analysis, morphological class definition, anaphora resolution etc. The study covers natural language processing challenges, namely of an English sentence. The article describes formal and linguistic problems, which might arise during the process and which are connected with graphic, semantic, and syntactic ambiguity. The article provides the description of how the problems had been solved before the automatic syntactic analysis was applied and the way, such analysis methods could be helpful in developing new analysis algorithms today. The analysis focuses on the issues, blocking the basis for the natural language processing — parsing — the process of sentence analysis according to their structure, content and meaning, which aims to examine the grammatical structure of the sentence, the division of sentences into constituent components and defining links between them. The analysis identifies a number of linguistic issues that will contribute to the development of an improved model of automatic syntactic analysis: lexical and grammatical synonymy and homonymy, hypo- and hyperonymy, lexical and semantic fields, anaphora resolution, ellipsis, inversion etc. The scope of natural language processing reveals obvious directions for the improvement of parsing models. The improvement will consequently expand the scope and improve the results in areas that already employ automatic parsing. Indispensable achievements in vocabulary and morphology processing shall not be neglected while improving automatic syntactic analysis mechanisms for natural languages.

Parsing Bangla Grammar Using Context Free Grammar

2013 ◽  
pp. 137-154 ◽  
Author(s):  
Al-Mahmud ◽  
Bishnu Sarker ◽  
K. M. Azharul Hasan
Keyword(s):  
Natural Language ◽  
Computational Linguistics ◽  
Language Processing ◽  
Top Down ◽  
Context Free Grammar ◽  
Context Free ◽  
Parse Table

Parsing plays a very prominent role in computational linguistics. Parsing a Bangla sentence is a primary need in Bangla language processing. This chapter describes the Context Free Grammar (CFG) for parsing Bangla language, and hence, a Bangla parser is proposed based on the Bangla grammar. This approach is very simple to apply in Bangla sentences, and the method is well accepted for parsing grammar. This chapter introduces a parser for Bangla language, which is, by nature, a predictive parser, and the parse table is constructed for recognizing Bangla grammar. Parse table is an important tool to recognize syntactical mistakes of Bangla sentences when there is no entry for a terminal in the parse table. If a natural language can be successfully parsed then grammar checking of this language becomes possible. The parsing scheme in this chapter works based on a top-down parsing method. CFG suffers from a major problem called left recursion. The technique of left factoring is applied to avoid the problem.

scholarly journals Hash Tables for a Digital Lexicon

2021 ◽  
Vol 28 (2) ◽  
pp. 25-38
Author(s):  
Fábio Carlos Moreno ◽  
Cinthyan Sachs C. de Barbosa ◽  
Edio Roberto Manfio
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Data Structures ◽  
Response Speed ◽  
Hash Tables ◽  
Processing Data ◽  
Natural Language Interface ◽  
Performance Results ◽  
And Storage

This paper deals with the construction of digital lexicons within the scope of Natural Language Processing. Data Structures called Hash Tables have demonstrated to generate good results for Natural Language Interface for Databases and have data dispersion, response speed and programming simplicity as main features. The storage of the desired information is done by associating a key through the hashing functions that is responsible for distributing the information in this table. The objective of this paper is to present the tool called Visual TaHs that uses a sparse table to a real lexicon (Lexicon of Herbs), improving performance results of several implemented hash functions. Such structure has achieved satisfactory results in terms of speed and storage when compared to conventional databases and can work in various media, such as desktop, Web and mobile.

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
Sign in / Sign up

Export Citation Format

Share Document