Rancang Bangun Aplikasi Chatbot Sebagai Media Pencarian Informasi Anime Menggunakan Regular Expression Pattern Matching

2017 ◽  
Vol 9 (1) ◽  
pp. 19-24 ◽  
Author(s):  
David Domarco ◽  
Ni Made Satvika Iswari
Keyword(s):  
Information Retrieval ◽  
Expression Pattern ◽  
Pattern Matching ◽  
Language Processing ◽  
Regular Expression ◽  
Technology Development ◽  
Data Retrieval ◽  
Index Terms ◽  
Retrieval Engine ◽  
Behavioral Intention To Use

Technology development has affected many areas of life, especially the entertainment field. One of the fastest growing entertainment industry is anime. Anime has evolved as a trend and a hobby, especially for the population in the regions of Asia. The number of anime fans grow every year and trying to dig up as much information about their favorite anime. Therefore, a chatbot application was developed in this study as anime information retrieval media using regular expression pattern matching method. This application is intended to facilitate the anime fans in searching for information about the anime they like. By using this application, user can gain a convenience and interactive anime data retrieval that can’t be found when searching for information via search engines. Chatbot application has successfully met the standards of information retrieval engine with a very good results, the value of 72% precision and 100% recall showing the harmonic mean of 83.7%. As the application of hedonic, chatbot already influencing Behavioral Intention to Use by 83% and Immersion by 82%. Index Terms—anime, chatbot, information retrieval, Natural Language Processing (NLP), Regular Expression Pattern Matching

Automatic Keyword Annotation System Using Newspapers

2014 ◽  
Vol 18 (3) ◽  
pp. 340-346 ◽  
Author(s):  
Tomoki Takada ◽  
◽  
Mizuki Arai ◽  
Tomohiro Takagi
Keyword(s):  
Information Retrieval ◽  
Language Processing ◽  
High Speed ◽  
Naive Bayes ◽  
High Accuracy ◽  
Naïve Bayes ◽  
Annotation System ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Index Terms

Nowadays, an increasingly large amount of information exists on the web. Therefore, a method is needed that enables us to find necessary information quickly because this is becoming increasingly difficult for users. To solve this problem, information retrieval systems like Google and recommendation systems like that on Amazon are used. In this paper, we focus on information retrieval systems. These retrieval systems require index terms, which affect the precision of retrieval. Two methods generally decide index terms. One is analyzing a text using natural language processing and deciding index terms using varying amounts of statistics. The other is someone choosing document keywords as index terms. However, the latter method requires too much time and effort and becomes more impractical as information grows. Therefore, we propose the Nikkei annotator system, which is based on the model of the human brain and learns patterns of past keyword annotation and automatically outputs keywords that users prefer. The purposes of the proposed method are automating manual keyword annotation and achieving high speed and high accuracy keyword annotation. Experimental results showed that the proposed method is more accurate than TFIDF and Naive Bayes in P@5 and P@10. Moreover, these results also showed that the proposed method could annotate about 19 times faster than Naive Bayes.

scholarly journals An Efficient Regular Expression Pattern Matching Using Stride Finite Automata

2019 ◽  
Vol 8 (6S) ◽  
pp. 1050-1054
Keyword(s):  
Expression Pattern ◽  
Pattern Matching ◽  
Regular Expression ◽  
Finite Automata

Example coordinating assumes a key job in different parcel payload identification applications, for example, interruption location, which is utilized in distinguishing the malware content in system frameworks. Various calculations and instruments have been created to improve reality complexities of distinguishing regex principles and subsequently empower profound bundle review at line rate. In this paper, a novel quickening plan is introduced to determine speed and space wasteful aspects of the customary automata and the DFA called multi-walk Finite automata that confirms more than one byte that expands the general execution of not just design matching but additionally string coordinating

Spam Filter Situs Jejaring Sosial Mahasiswa Menggunakan Regular Expression

2018 ◽  
Vol 8 (2) ◽  
pp. 69-73 ◽  
Author(s):  
Simon Salomon ◽  
Seng Hansun
Keyword(s):  
Social Networking ◽  
Behavioral Intention ◽  
Regular Expression ◽  
Mean Value ◽  
Intention To Use ◽  
User Interest ◽  
Spam Filter ◽  
Information And Communication ◽  
Index Terms ◽  
Behavioral Intention To Use

Spam is an unexpected and unsolicited email sent randomly indiscriminately, directly or indirectly by the sender who has no connection whatsoever with the recipient. The purpose of spam itself is to send information to the recipient, where the content of the sent message generally contains ads that offer nonessential products or illegal products, scams, promotional purposes, or spreading malware designed to hijack computers receiver. Based on the background of the problem, it is necessary anti-spam on a chat or dissemination of information in social networking using regular expression. From this study, the behavioral intention to use at level of 80% means that the user agrees that this website increases user interest in obtaining information and communication, and generates an immersion level of 80% which means the user is very focused when using the website. This website generates value by 98% precision and 98% recall that produce harmonic mean value of 97% so that it can be concluded that it has the precision and recall value harmonious. Index Terms—social networking, regular expression, spam, website

PENERAPAN NATURAL LANGUAGE PROCESSING BERBASIS VIRTUAL ASSISTANT PADA BAGIAN ADMINISTRASI AKADEMIK STMIK DHARMA WACANA

2021 ◽  
Vol 5 (1) ◽  
pp. 33-47
Author(s):  
Arief Adjie Wicaksono ◽  
Ridwan Yusuf ◽  
Tri Aristi Saputri
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Pattern Matching ◽  
Language Processing ◽  
Regular Expression

Sekolah Tinggi Ilmu Manajemen Informatika dan Komputer (STMIK) Dharma Wacana memiliki beberapa bagian seperti Bagian Administrasi Akademik yang memiliki tugas melaksanakan pelayanan dibidang akademik. Bagian Administrasi Akademik menjadi sumber informasi terkait kegiatan perkuliahan. Kebutuhan informasi perkuliahan belum efektif dikarenakan terbatasnya jam kerja dari pegawai dan masih banyak pertanyaan berulang yang berdatangan ke Bagian Administrasi Akademik, seperti pertanyaan yang telah ditanyakan oleh seorang mahasiswa kemudian ditanyakan lagi oleh mahasiswa lainnya. Tujuan dari penelitian ini adalah melakukan observasi dan wawancara terhadap mahasiswa dan pegawai Bagian Administrasi Akademik serta menganalisis kelemahannya sehingga dapat menjadi acuan untuk merancang aplikasi dengan penerapan Natural Language Processing (NLP). Pada penelitian telah dibangun Virtual Assistant berupa Chatbot yang tersedia pada platform messenger yaitu LINE, Facebook dan Telegram yang hanya bertindak layaknya bagian informasi perkuliahan. NLP dengan pendekatan pattern matching menggunakan regular expression diterapkan dalam proses mengenali pertanyaan mahasiswa sehingga Virtual Assistant dapat memberikan jawaban yang sesuai.

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