Log in

Relevant bibliographies by topics / Word2Vee / Journal articles

To see the other types of publications on this topic, follow the link: Word2Vee.

Journal articles on the topic 'Word2Vee'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Word2Vee.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Romanyuk, Andriy. "Vector Representations of Ukrainian Words." Ukraina Moderna 27, no. 27 (2019): 46–72. http://dx.doi.org/10.30970/uam.2019.27.1062.

Full text

Abstract:

I n this paper, Ukrainian word embeddings and their properties are examined. Provided are a theoretical description, a brief account of the most common technologies used to produce an embedding, and lists of implemented algorithms. Word2wec, the first technology for calculating word embeddings, is used to demonstrate modern approaches of calculating using neural networks. Word2wec and FastText, which evolved from word2vec, are compared, and FastText’s benefits are described. Word embeddings have been applied to solving majority of the practical tasks of natural language processing. One of the

APA, Harvard, Vancouver, ISO, and other styles

2

CHURCH, KENNETH WARD. "Word2Vec." Natural Language Engineering 23, no. 1 (2016): 155–62. http://dx.doi.org/10.1017/s1351324916000334.

Full text

Abstract:

AbstractMy last column ended with some comments about Kuhn and word2vec. Word2vec has racked up plenty of citations because it satisifies both of Kuhn’s conditions for emerging trends: (1) a few initial (promising, if not convincing) successes that motivate early adopters (students) to do more, as well as (2) leaving plenty of room for early adopters to contribute and benefit by doing so. The fact that Google has so much to say on ‘How does word2vec work’ makes it clear that the definitive answer to that question has yet to be written. It also helps citation counts to distribute code and data

APA, Harvard, Vancouver, ISO, and other styles

3

Tomomi, HASHIMOTO, and TAO Xingyu. "Chatbot using word2vec." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2020 (2020): 1P2—E01. http://dx.doi.org/10.1299/jsmermd.2020.1p2-e01.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Rusli, Muhammad. "EKSTRAKSI FITUR MENGGUNAKAN MODEL WORD2VEC PADA SENTIMENT ANALYSIS KOLOM KOMENTAR KUISIONER EVALUASI DOSEN OLEH MAHASISWA." KLIK - KUMPULAN JURNAL ILMU KOMPUTER 7, no. 1 (2020): 35. http://dx.doi.org/10.20527/klik.v7i1.296.

Full text

Abstract:

<p><em>This research is about Sentiment Analysis using the Word2vec model. this research was conducted by Fauzi (2019). But in his research the use of the Word2vec model produces an accuracy of 70%, because the data used is small. In little data Word2vec cannot grasp the similarity of meaning well. So that related research was conducted which used lecturer evaluation comment data and also Wikipedia article data in Indonesian language as Word2vec model. In this study a comparison of average extraction features of Word2vec and Bag of Centroid base Word2vec was done and a combination

APA, Harvard, Vancouver, ISO, and other styles

5

Li, Bofang, Aleksandr Drozd, Yuhe Guo, Tao Liu, Satoshi Matsuoka, and Xiaoyong Du. "Scaling Word2Vec on Big Corpus." Data Science and Engineering 4, no. 2 (2019): 157–75. http://dx.doi.org/10.1007/s41019-019-0096-6.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Rathore, Mohit, Dikshant Gupta, and Dinabandhu Bhandari. "Complaint Classification using Word2Vec Model." International Journal of Engineering & Technology 7, no. 4.5 (2018): 402. http://dx.doi.org/10.14419/ijet.v7i4.5.20192.

Full text

Abstract:

Attempt has been made to develop a versatile, universal complaint grievance segregator by classifying orally acknowledged grievancesinto one of the predefined categories. The oral complaints are first converted to text and then each word is represented by a vector usingword2vec. Each grievance is represented by a single vector using Gated Recurrent Unit (GRU) that implements the hidden state of Recurrent Neural Network (RNN) model. The popular Multi-Layer Perceptron (MLP) has been used as the classifier to identify the categories.

APA, Harvard, Vancouver, ISO, and other styles

7

Idris, Muhammad, Ahmad Rifai, and Ken Ditha Tania. "Sentiment Analysis of Tokopedia App Reviews using Machine Learning and Word Embeddings." sinkron 9, no. 1 (2025): 210–19. https://doi.org/10.33395/sinkron.v9i1.14278.

Full text

Abstract:

Tokopedia, a prominent e-commerce platform in Indonesia, generates vast amounts of user feedback, offering valuable insights into customer satisfaction through sentiment analysis. However, sentiment analysis of app reviews specifically on Tokopedia reviews remains underexplored. Sentiment analysis, also known as opinion mining, categorizes user sentiments into positive or negative, offering insights into user preferences and service shortcomings. While traditional text representation techniques like TF-IDF are widely used for sentiment analysis, they lack the semantic richness provided by adva

APA, Harvard, Vancouver, ISO, and other styles

8

Iskandar, Dede, and Ana Kurniawati. "Analisis Perbandingan Teknik Word2vec dan Doc2vec dalam Mengukur Kemiripan Dokumen Menggunakan Cosine Similarity." Jurnal Teknologi Informasi dan Ilmu Komputer 12, no. 1 (2025): 133–44. https://doi.org/10.25126/jtiik.20251219143.

Full text

Abstract:

Tempatkan Era digital memudahkan akses dokumen online dalam jumlah besar menjadi lebih mudah dan cepat, namun juga menimbulkan tantangan kompleks dalam pengelolaan dan analisis informasi. Salah satu tantangan utama adalah mengukur kemiripan antar dokumen, yang penting untuk berbagai aplikasi seperti deteksi plagiarisme. Menanggapi tantangan ini, banyak teknik yang dapat digunakan dalam merepresentasikan dokumen menjadi vektor untuk mengukur kemiripan dokumen. Dalam penelitian ini teknik Word2vec dan Doc2vec digunakan untuk merepresentasikan dokumen menjadi vektor, dan dalam mengukur kemiripan

APA, Harvard, Vancouver, ISO, and other styles

9

Iskandar, Dede, and Ana Kurniawati. "Analisis Perbandingan Teknik Word2vec dan Doc2vec dalam Mengukur Kemiripan Dokumen Menggunakan Cosine Similarity." Jurnal Teknologi Informasi dan Ilmu Komputer 12, no. 1 (2025): 133–44. https://doi.org/10.25126/jtiik.2025129143.

Full text

Abstract:

Tempatkan Era digital memudahkan akses dokumen online dalam jumlah besar menjadi lebih mudah dan cepat, namun juga menimbulkan tantangan kompleks dalam pengelolaan dan analisis informasi. Salah satu tantangan utama adalah mengukur kemiripan antar dokumen, yang penting untuk berbagai aplikasi seperti deteksi plagiarisme. Menanggapi tantangan ini, banyak teknik yang dapat digunakan dalam merepresentasikan dokumen menjadi vektor untuk mengukur kemiripan dokumen. Dalam penelitian ini teknik Word2vec dan Doc2vec digunakan untuk merepresentasikan dokumen menjadi vektor, dan dalam mengukur kemiripan

APA, Harvard, Vancouver, ISO, and other styles

10

Sumantri, Galang, and Bambang Sumarno Hadi Marwoto. "ANALISIS SENTIMEN DI TWITTER TERKAIT TIM NASIONAL SEPAK BOLA INDONESIA MENGGUNAKAN METODE SUPPORT VECTOR MACHINE." Jurnal Kajian dan Terapan Matematika 10, no. 2 (2024): 96–104. https://doi.org/10.21831/jktm.v10i2.19561.

Full text

Abstract:

AbstrakTimnas sepak bola Indonesia sering gagal bersaing di berbagai turnamen besar internasional. Sentimen masyarakat terhadap prestasi Timnas yang diekspresikan melalui twitter dapat digunakan sebagai salah satu cara untuk menilai perkembangan sepak bola di Indonesia. Penelitian ini bertujuan untuk mengetahui performa metode Support Vektor Machine (SVM) dengan ekstrasi fitur word embeddings Word2vec dan FastText dalam analisis sentimen terkait Timnas sepak bola Indonesia. Data dalam penelitian ini menggunakan data teks berupa tweet terkait keikutsertaan Timnas di ajang piala AFF tahun 2018,

APA, Harvard, Vancouver, ISO, and other styles

11

Kang, Hyungsuc, and Janghoon Yang. "Optimization of Word2vec Models for Korean Word Embeddings." Journal of Digital Contents Society 20, no. 4 (2019): 825–33. http://dx.doi.org/10.9728/dcs.2019.20.4.825.

Full text

APA, Harvard, Vancouver, ISO, and other styles

12

Kang, Hyungsuc, and Janghoon Yang. "Performance Comparison of Word2vec and fastText Embedding Models." Journal of Digital Contents Society 21, no. 7 (2020): 1335–43. http://dx.doi.org/10.9728/dcs.2020.21.7.1335.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Zhang, Ziheng, Feng Han, Hongjian Zhang, Tomohiro Aoki, and Katsuhiko Ogasawara. "Examining the Effect of the Ratio of Biomedical Domain to General Domain Data in Corpus in Biomedical Literature Mining." Applied Sciences 12, no. 1 (2021): 154. http://dx.doi.org/10.3390/app12010154.

Full text

Abstract:

Biomedical terms extracted using Word2vec, the most popular word embedding model in recent years, serve as the foundation for various natural language processing (NLP) applications, such as biomedical information retrieval, relation extraction, and recommendation systems. The objective of this study is to examine how changes in the ratio of the biomedical domain to general domain data in the corpus affect the extraction of similar biomedical terms using Word2vec. We downloaded abstracts of 214,892 articles from PubMed Central (PMC) and the 3.9 GB Billion Word (BW) benchmark corpus from the com

APA, Harvard, Vancouver, ISO, and other styles

14

Islamanda, Muhammad Dinan, and Yuliant Sibaroni. "Whoosh User Sentiment Analysis on Social Media Using Word2Vec and the Best Naïve Bayes Probability Model." sinkron 8, no. 3 (2024): 1558–68. http://dx.doi.org/10.33395/sinkron.v8i3.13742.

Full text

Abstract:

By using the Twitter microblogging feature, users can post short tweets with limited characters that express their thoughts and opinions regarding a matter. The newest transportation in Indonesia, a high-speed train namely Whoosh is one of the things that Twitter users responded to. This latest transportation has led to the emergence of opinions from the Indonesian people which are shared publicly in various media, one of which is social media. Therefore, to make it easier for business people or companies to understand public opinion regarding service improvements in the future, sentiment anal

APA, Harvard, Vancouver, ISO, and other styles

15

Alvi Rahmy Royyan and Erwin Budi Setiawan. "Feature Expansion Word2Vec for Sentiment Analysis of Public Policy in Twitter." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 6, no. 1 (2022): 78–84. http://dx.doi.org/10.29207/resti.v6i1.3525.

Full text

Abstract:

Social media users, especially on Twitter, can freely express opinions or other information in the form of tweets about anything, including responding to a public policy. In a written tweet, there is a limit of 280 characters per tweet and this allows for problems such as vocabulary mismatches. Therefore, in this study, the feature expansion Word2vec method was applied to overcome when the vocabulary mismatches occur. This study develops and compares the Twitter sentiment analysis system using the feature expansion Word2vec method with the Logistic Regression (LR) and Support Vector Machine (S

APA, Harvard, Vancouver, ISO, and other styles

16

Botov, D. S., J. D. Klenin, and I. E. Nikolaev. "Information extraction using neural language models for the case of online job listings analysis." Yugra State University Bulletin 14, no. 3 (2018): 37–48. http://dx.doi.org/10.17816/byusu2018037-48.

Full text

Abstract:

In this article we discuss the approach to information extraction (IE) using neural language models. We provide a detailed overview of modern IE methods: both supervised and unsupervised. The proposed method allows to achieve a high quality solution to the problem of analyzing the relevant labor market requirements without the need for a time-consuming labelling procedure. In this experiment, professional standards act as a knowledge base of the labor domain. Comparing the descriptions of work actions and requirements from professional standards with the elements of job listings, we extract fo

APA, Harvard, Vancouver, ISO, and other styles

17

Pertiwi, Ayu, Azhari Azhari, and Sri Mulyana. "Fast2Vec, a modified model of FastText that enhances semantic analysis in topic evolution." PeerJ Computer Science 11 (May 19, 2025): e2862. https://doi.org/10.7717/peerj-cs.2862.

Full text

Abstract:

Background Topic modeling approaches, such as latent Dirichlet allocation (LDA) and its successor, the dynamic topic model (DTM), are widely used to identify specific topics by extracting words with similar frequencies from documents. However, these topics often require manual interpretation, which poses challenges in constructing semantics topic evolution, mainly when topics contain negations, synonyms, or rare terms. Neural network-based word embeddings, such as Word2vec and FastText, have advanced semantic understanding but have their limitations. Word2Vec struggles with out-of-vocabulary (

APA, Harvard, Vancouver, ISO, and other styles

18

Onsu, Romario, Daniel Febrian Sengkey, and Feisy Diane Kambey. "Implementasi Bi-LSTM dengan Ekstraksi Fitur Word2Vec untuk Pengembangan Analisis Sentimen Aplikasi Identitas Kependudukan Digital." Jurnal Teknologi Terpadu 10, no. 1 (2024): 46–55. http://dx.doi.org/10.54914/jtt.v10i1.1225.

Full text

Abstract:

Pemerintah Indonesia berupaya meningkatkan layanan publik berbasis digital, termasuk aplikasi Identitas Kependudukan Digital (IKD) yang diluncurkan pada 2022 oleh Dirjen Kependudukan dan Pencatatan Sipil. Sejak diluncurkan, IKD mendapat berbagai tanggapan dari masyarakat. Data ulasan di Google Play Store menunjukkan penurunan rating dari Juni hingga Desember 2023. Analisis ulasan penting untuk memahami kepuasan pengguna dan mengidentifikasi masalah serta memandu perbaikan aplikasi. Penelitian ini bertujuan melakukan analisis sentimen ulasan pengguna IKD menggunakan metode Bidirectional Long Sh

APA, Harvard, Vancouver, ISO, and other styles

19

Rifaldy, Fadil, Yuliant Sibaroni, and Sri Suryani Prasetiyowati. "Effectiveness of Word2Vec and TF-IDF in Sentiment Classification on Online Investment Platforms Using Support Vector Machine." JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) 10, no. 2 (2025): 863–74. https://doi.org/10.29100/jipi.v10i2.6055.

Full text

Abstract:

Investing in Indonesia is increasingly popular, especially among the millennial generation. investments such as deposits, gold, stocks, and online investment applications are increasingly in demand. This research focuses on the sentiment classification of user reviews of the Nanovest online investment application on the Google Play Store using the Support Vector Machine (SVM) method. SVM is used because it can classify opinions into positive and negative sentiment classes with good accuracy, by evaluating how effective Word2Vec features extraction that can convert words in a text into numerica

APA, Harvard, Vancouver, ISO, and other styles

20

Ferriyan, Andrey, Achmad Husni Thamrin, Keiji Takeda, and Jun Murai. "Encrypted Malicious Traffic Detection Based on Word2Vec." Electronics 11, no. 5 (2022): 679. http://dx.doi.org/10.3390/electronics11050679.

Full text

Abstract:

Network-based intrusion detections become more difficult as Internet traffic is mostly encrypted. This paper introduces a method to detect encrypted malicious traffic based on the Transport Layer Security handshake and payload features without waiting for the traffic session to finish while preserving privacy. Our method, called TLS2Vec, creates words from the extracted features and uses Long Short-Term Memory (LSTM) for inference. We evaluated our method using traffic from three malicious applications and a benign application that we obtained from two publicly available datasets. Our results

APA, Harvard, Vancouver, ISO, and other styles

21

Agrawal, Rashmi, and Rinkaj Goyal. "Developing bug severity prediction models using word2vec." International Journal of Cognitive Computing in Engineering 2 (June 2021): 104–15. http://dx.doi.org/10.1016/j.ijcce.2021.08.001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

22

Yousuf, Hana, Asma Qassem Al-Hamad, and Said Salloum. "An Overview on CryptDb and Word2vec Approaches." Advances in Science, Technology and Engineering Systems Journal 5, no. 5 (2020): 1282–87. http://dx.doi.org/10.25046/aj0505154.

Full text

APA, Harvard, Vancouver, ISO, and other styles

23

Марценюк, К., та А. Деведжіогуллари. "Оцінювання неструктурованих резюме за допомогою моделі Word2Vec". Адаптивні системи автоматичного управління 2, № 45 (2024): 134–42. http://dx.doi.org/10.20535/1560-8956.45.2024.313139.

Full text

Abstract:

Об'єктом дослідження є модель обробки природної мови Word2Vec. У статті представлено огляд основних принципів, на яких базується ця модель, а також проведено порівняльний експеримент з оцінки її ефективності у контексті неструктурованих резюме. Метою роботи є підвищення ефективності та точності автоматизованих систем відбору кандидатів на роботу. Пропонується використання моделі Word2Vec, яка, на відміну від традиційних методів, таких як TF-IDF, здатна враховувати семантичні зв'язки між словами. Це дозволяє системі точніше оцінювати кандидатів, беручи до уваги не лише прямі співпадіння навичок

APA, Harvard, Vancouver, ISO, and other styles

24

Jo, Seokyeon, Kyungmin Kwon, and Hanjun Lee. "Research Trend Analysis using Word2Vec and Entropy." Korean Data Analysis Society 26, no. 4 (2024): 1051–63. http://dx.doi.org/10.37727/jkdas.2024.26.4.1051.

Full text

Abstract:

To understand trends in a specific research field, qualitative literature analysis of major papers published in that field has traditionally been used. Recently, there has been an increasing effort to quantitatively analyze large volumes of literature using text analysis techniques. This study proposes an analysis method utilizing word embedding and entropy. The proposed method is applied to analyze literature in the field of Management Information Systems (MIS). For this purpose, 12,704 papers published in major MIS journals were collected. Word2Vec and annual keyword clustering were applied

APA, Harvard, Vancouver, ISO, and other styles

25

Ji, Shihao, Nadathur Satish, Sheng Li, and Pradeep K. Dubey. "Parallelizing Word2Vec in Shared and Distributed Memory." IEEE Transactions on Parallel and Distributed Systems 30, no. 9 (2019): 2090–100. http://dx.doi.org/10.1109/tpds.2019.2904058.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Chengzhang, Xu, and Liu Dan. "Chinese Text Summarization Algorithm Based on Word2vec." Journal of Physics: Conference Series 976 (February 2018): 012006. http://dx.doi.org/10.1088/1742-6596/976/1/012006.

Full text

APA, Harvard, Vancouver, ISO, and other styles

27

Naymushin, M. "Word2vec semantic model and human language processing." Речевые технологии, no. 1-2 (2021): 47–60. http://dx.doi.org/10.58633/2305-8129_2021_1-2_47.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

Ozer, Zeynep, Ilyas Ozer, and Oguz Findik. "Diacritic restoration of Turkish tweets with word2vec." Engineering Science and Technology, an International Journal 21, no. 6 (2018): 1120–27. http://dx.doi.org/10.1016/j.jestch.2018.09.002.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Dewanda, Kaisul Fuqara, Weny Mistarika Rahmawati, Septiyawan Rosetya Wardhana, and Gusti Eka Yuliastuti. "Penentuan Relevansi Artikel Ilmiah dengan Metode Word2Vec." KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika 3, no. 2 (2023): 9–16. http://dx.doi.org/10.31284/j.kernel.2022.v3i2.4038.

Full text

Abstract:

ArXiv merupakan tempat menyimpan pracetak elektronik termasuk artikel ilmiah dan dapat diakses oleh semua pengguna internet secara online. Seiring berjalannya waktu, dokumen artikel ilmiah makin bertambah banyak. Hal tersebut dapat menurunkan tingkat efektifitas pengelompokkan artikel ilmiah berdasarkan bidang keminatan pengguna. Suatu sistem rekomendasi diperlukan untuk penentuan relevansi artikel ilmiah dapat memberi pengguna rekomendasi artikel ilmiah yang sesuai bidang keminatan pengguna, sehingga pengguna akan lebih mudah dalam mengakses artikel ilmiah pada sistem tersebut. Penulis akan m

APA, Harvard, Vancouver, ISO, and other styles

30

Wang, Jin, Yangning Tang, Shiming He, et al. "LogEvent2vec: LogEvent-to-Vector Based Anomaly Detection for Large-Scale Logs in Internet of Things." Sensors 20, no. 9 (2020): 2451. http://dx.doi.org/10.3390/s20092451.

Full text

Abstract:

Log anomaly detection is an efficient method to manage modern large-scale Internet of Things (IoT) systems. More and more works start to apply natural language processing (NLP) methods, and in particular word2vec, in the log feature extraction. Word2vec can extract the relevance between words and vectorize the words. However, the computing cost of training word2vec is high. Anomalies in logs are dependent on not only an individual log message but also on the log message sequence. Therefore, the vector of words from word2vec can not be used directly, which needs to be transformed into the vecto

APA, Harvard, Vancouver, ISO, and other styles

31

Af'idah, Dwi Intan, Dairoh Dairoh, Sharfina Febbi Handayani, and Riszki Wijayatun Pratiwi. "Pengaruh Parameter Word2Vec terhadap Performa Deep Learning pada Klasifikasi Sentimen." Jurnal Informatika: Jurnal Pengembangan IT 6, no. 3 (2021): 156–61. http://dx.doi.org/10.30591/jpit.v6i3.3016.

Full text

Abstract:

The difficulty of sentiment classification on this big data can be overcome using deep learning. Before the deep learning training and testing process is carried out, a word features extraction process is needed. Word2Vec as a word features extraction is often used in sentiment classification pre-training because it can capture the semantic meaning of the text by representing a similar vector for each word that has a close meaning. Word2Vec has three parameters that affect the model learning process namely architecture, evaluation method, and dimensions. This study aims to determine the effect

APA, Harvard, Vancouver, ISO, and other styles

32

Siti Khomsah, Rima Dias Ramadhani, and Sena Wijaya. "The Accuracy Comparison Between Word2Vec and FastText On Sentiment Analysis of Hotel Reviews." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 6, no. 3 (2022): 352–58. http://dx.doi.org/10.29207/resti.v6i3.3711.

Full text

Abstract:

Word embedding vectorization is more efficient than Bag-of-Word in word vector size. Word embedding also overcomes the loss of information related to sentence context, word order, and semantic relationships between words in sentences. Several kinds of Word Embedding are often considered for sentiment analysis, such as Word2Vec and FastText. Fast Text works on N-Gram, while Word2Vec is based on the word. This research aims to compare the accuracy of the sentiment analysis model using Word2Vec and FastText. Both models are tested in the sentiment analysis of Indonesian hotel reviews using the da

APA, Harvard, Vancouver, ISO, and other styles

33

Af'idah, Dwi Intan, Dairoh Dairoh, Sharfina Febbi Handayani, Riszki Wijayatun Pratiwi, and Susi Indah Sari. "Sentimen Ulasan Destinasi Wisata Pulau Bali Menggunakan Bidirectional Long Short Term Memory." MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer 21, no. 3 (2022): 607–18. http://dx.doi.org/10.30812/matrik.v21i3.1402.

Full text

Abstract:

Pemerintah dan pelaku industri pariwisata mengalami permasalahan dalam menentukan prioritas pengembangan suatu destinasi wisata. Karena itu, diperlukan identifikasi objek wisata yang diminati namun banyak mendapat ulasan buruk melalui ulasan dari masyarakat yang tersebar di internet. Penelitian ini bertujuan melakukan analisis sentimen terhadap ulasan objek wisata di Pulau Bali menggunakan Bi-LSTM dan Word2Vec, sehingga diperoleh model terbaik yang dapat digunakan untuk mengidentifikasi objek wisata potensial namun mendapat ulasan buruk. Bi-LSTM merupakan deep learning yang menawarkan akurasi

APA, Harvard, Vancouver, ISO, and other styles

34

Cahyana, Nur Heri, Yuli Fauziah, Wisnalmawati Wisnalmawati, Agus Sasmito Aribowo, and Shoffan Saifullah. "The Evaluation of Effects of Oversampling and Word Embedding on Sentiment Analysis." JURNAL INFOTEL 17, no. 1 (2025): 54–67. https://doi.org/10.20895/infotel.v17i1.1077.

Full text

Abstract:

Generally, opinion datasets for sentiment analysis are in an unbalanced condition. Unbalanced data tends to have a bias in favor of classification in the majority class. Data balancing by adding synthetic data to the minority class requires an oversampling strategy. This research aims to overcome this imbalance by combining oversampling and word embedding (Word2Vec or FastText). We convert the opinion dataset into a sentence vector, and then an oversampling method is applied here. We use 5 (five) datasets from comments on YouTube videos with several differences in terms, number of records, and

APA, Harvard, Vancouver, ISO, and other styles

35

Khan, Muhammad Shehrayar, Atif Rizwan, Muhammad Shahzad Faisal, Tahir Ahmad, Muhammad Saleem Khan, and Ghada Atteia. "Identification of Review Helpfulness Using Novel Textual and Language-Context Features." Mathematics 10, no. 18 (2022): 3260. http://dx.doi.org/10.3390/math10183260.

Full text

Abstract:

With the increase in users of social media websites such as IMDb, a movie website, and the rise of publicly available data, opinion mining is more accessible than ever. In the research field of language understanding, categorization of movie reviews can be challenging because human language is complex, leading to scenarios where connotation words exist. Connotation words have a different meaning than their literal meanings. While representing a word, the context in which the word is used changes the semantics of words. In this research work, categorizing movie reviews with good F-Measure score

APA, Harvard, Vancouver, ISO, and other styles

36

Aydoğan Kılıç, Dilek, Deniz Kenan Kılıç, and Izabela Ewa Nielsen. "Comparative study of feature extraction methods for automated ICD code classification using MIMIC-III medical notes and deep learning models." Mathematical Modelling and Numerical Simulation with Applications 5, no. 2 (2025): 421–50. https://doi.org/10.53391/mmnsa.1666223.

Full text

Abstract:

ICD standardizes diagnosis codes globally, aiding payments, research, planning, and quality management. Its complexity leads to longer exams, higher training costs, increased workforce needs, coding errors, and unreliable data. Automated ICD systems using ML address these issues. Long medical notes complicate ML, making feature extraction crucial for efficient ICD classification. Despite numerous studies, no systematic analysis of feature extraction methods, especially in deep learning (DL), exists. The MIMIC-III dataset is used with two preprocessing combinations, fundamental and advanced. TF

APA, Harvard, Vancouver, ISO, and other styles

37

Kang, Hyungsuc, and Janghoon Yang. "Analyzing Semantic Relations of Word Vectors trained by The Word2vec Model." Journal of KIISE 46, no. 10 (2019): 1088–93. http://dx.doi.org/10.5626/jok.2019.46.10.1088.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Suhana, S. Sumaya, and S. Ashok Kumar. "An Enhancement in Machine Learning Approaches for Novel Data Mining Serendipitous Drug Usage to Reduce False Positive Rate from Social Media Comparing Word2vec Algorithm." ECS Transactions 107, no. 1 (2022): 13329–44. http://dx.doi.org/10.1149/10701.13329ecst.

Full text

Abstract:

The aim is mining serendipitous drug usage to reduce the false-positive rate from social media. Materials and Methods: Two machine learning algorithms Knn classifier with the sample size = 12 and word2vec algorithm with sample size = 12. Results and Discussion: The knn algorithm has shown more accuracy of (93.91%) in reducing the false positive rates when compared with word2vec algorithm accuracy (87.50%). By using the G-power tool, the pre-test calculated with a g-power value = 80% and threshold 0.05% confidence interval of 95% mean and standard deviation. Conclusion: It is found that the knn

APA, Harvard, Vancouver, ISO, and other styles

39

Adrian, Muhammad Ghifari, Sri Suryani Prasetyowati, and Yuliant Sibaroni. "Effectiveness of Word Embedding GloVe and Word2Vec within News Detection of Indonesian uUsing LSTM." JURNAL MEDIA INFORMATIKA BUDIDARMA 7, no. 3 (2023): 1180. http://dx.doi.org/10.30865/mib.v7i3.6411.

Full text

Abstract:

In recent years the use of social media platforms in Indonesia has continued to increase. The increasing use of social media has several advantages and disadvantages. The advantage is that the news is easily accessible by anyone, while the disadvantage is that much information that is spread is hoax news. Hoax news must be detected because hoax news spreads false and misleading information. This undermines the integrity of the information and needs to be clarified for the public. By detecting hoax news, we can ensure the information being disseminated is accurate and trustworthy. In this study

APA, Harvard, Vancouver, ISO, and other styles

40

Liaquathali, Shaheetha, and Vadivazhagan Kadirvelu. "Integration of natural language processing methods and machine learning model for malicious webpage detection based on web contents." IAES International Journal of Robotics and Automation (IJRA) 14, no. 1 (2025): 47. https://doi.org/10.11591/ijra.v14i1.pp47-57.

Full text

Abstract:

Malicious actors continually exploit vulnerabilities in web systems to distribute malware, launch phishing attacks, steal sensitive information, and perpetrate various forms of cybercrime. Traditional signature-based methods for detecting malicious webpages often struggle to keep pace with the rapid evolution of malware and cyber threats. As a result, there is a growing demand for more advanced and proactive approaches that can effectively identify malicious web content based on its characteristics and behavior. Detection based on web content is crucial because malicious webpages can be design

APA, Harvard, Vancouver, ISO, and other styles

41

Nur Ghaniaviyanto Ramadhan. "Indonesian Online News Topics Classification using Word2Vec and K-Nearest Neighbor." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 5, no. 6 (2021): 1083–89. http://dx.doi.org/10.29207/resti.v5i6.3547.

Full text

Abstract:

News is information disseminated by newspapers, radio, television, the internet, and other media. According to the survey results, there are many news titles from various topics spread on the internet. This of course makes newsreaders have difficulty when they want to find the desired news topic to read. These problems can be solved by grouping or so-called classification. The classification process is carried out of course by using a computerized process. This study aims to classify several news topics in Indonesian language using the KNN classification model and word2vec to convert words int

APA, Harvard, Vancouver, ISO, and other styles

42

Lu, Zihao, Xiaohui Hu, and Yun Xue. "Dual-Word Embedding Model Considering Syntactic Information for Cross-Domain Sentiment Classification." Mathematics 10, no. 24 (2022): 4704. http://dx.doi.org/10.3390/math10244704.

Full text

Abstract:

The purpose of cross-domain sentiment classification (CDSC) is to fully utilize the rich labeled data in the source domain to help the target domain perform sentiment classification even when labeled data are insufficient. Most of the existing methods focus on obtaining domain transferable semantic information but ignore syntactic information. The performance of BERT may decrease because of domain transfer, and traditional word embeddings, such as word2vec, cannot obtain contextualized word vectors. Therefore, achieving the best results in CDSC is difficult when only BERT or word2vec is used.

APA, Harvard, Vancouver, ISO, and other styles

43

Iatsenko, D. V. "Texts Classification with the usage of Neural Network based on the Word2vec’s Words Representation." International Journal on Soft Computing 14, no. 2 (2023): 1–13. http://dx.doi.org/10.5121/ijsc.2023.14201.

Full text

Abstract:

Assigning the submitted text to one of the predetermined categories is required when dealing with application-oriented texts. There are many different approaches to solving this problem, including using neural network algorithms. This article explores using neural networks to sort news articles based on their category. Two word vectorization algorithms are being used — The Bag of Words (BOW) and the word2vec distributive semantic model. For this work the BOW model was applied to the FNN, whereas the word2vec model was applied to CNN. We have measured the accuracy of the classification when app

APA, Harvard, Vancouver, ISO, and other styles

44

Putra, Thariq Iskandar Zulkarnain Maulana, Suprapto Suprapto, and Arif Farhan Bukhori. "Model Klasifikasi Berbasis Multiclass Classification dengan Kombinasi Indobert Embedding dan Long Short-Term Memory untuk Tweet Berbahasa Indonesia." Jurnal Ilmu Siber dan Teknologi Digital 1, no. 1 (2022): 1–28. http://dx.doi.org/10.35912/jisted.v1i1.1509.

Full text

Abstract:

Purpose: This research aims to improve the performance of the text classification model from previous studies, by combining the IndoBERT pre-trained model with the Long Short-Term Memory (LSTM) architecture in classifying Indonesian-language tweets into several categories. Method: The classification text based on multiclass classification was used in this research, combined with pre-trained IndoBERT namely Long Short-Term Memory (LTSM). The dataset was taken using crawling method from API Twitter. Then, it will be compared with Word2Vec-LTSM and fined-tuned IndoBERT. Result: The IndoBERT-LSTM

APA, Harvard, Vancouver, ISO, and other styles

45

Fauzi, M. Ali. "Word2Vec model for sentiment analysis of product reviews in Indonesian language." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 1 (2019): 525–30. https://doi.org/10.11591/ijece.v9i1.pp525-530.

Full text

Abstract:

Online product reviews have become a source of greatly valuable information for consumers in making purchase decisions and producers to improve their product and marketing strategies. However, it becomes more and more difficult for people to understand and evaluate what the general opinion about a particular product in manual way since the number of reviews available increases. Hence, the automatic way is preferred. One of the most popular techniques is using machine learning approach such as Support Vector Machine (SVM). In this study, we explore the use of Word2Vec model as features in the S

APA, Harvard, Vancouver, ISO, and other styles

46

NADOYAMA, Natsuko, and Kazushi OKAMOTO. "Word2Vec Based Item Vector Learning from Purchase Data." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 29, no. 3 (2017): 579–85. http://dx.doi.org/10.3156/jsoft.29.3_579.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Kim, Woo-ju, Dong-he Kim, and Hee-won Jang. "Semantic Extention Search for Documents Using the Word2vec." Journal of the Korea Contents Association 16, no. 10 (2016): 687–92. http://dx.doi.org/10.5392/jkca.2016.16.10.687.

Full text

APA, Harvard, Vancouver, ISO, and other styles

48

Wang, Jin, Changqing Zhao, Shiming He, Yu Gu, Osama Alfarraj, and Ahed Abugabah. "LogUAD: Log Unsupervised Anomaly Detection Based on Word2Vec." Computer Systems Science and Engineering 41, no. 3 (2022): 1207–22. http://dx.doi.org/10.32604/csse.2022.022365.

Full text

APA, Harvard, Vancouver, ISO, and other styles

49

Yang, Ning, Guanyu Li, Hailan Ding, and Chunwei Gong. "Study on Tibetan Word Vector based on Word2vec." Journal of Physics: Conference Series 1187, no. 5 (2019): 052074. http://dx.doi.org/10.1088/1742-6596/1187/5/052074.

Full text

APA, Harvard, Vancouver, ISO, and other styles

50

Shao, Taihua, Honghui Chen, and Wanyu Chen. "Query Auto-Completion Based on Word2vec Semantic Similarity." Journal of Physics: Conference Series 1004 (April 2018): 012018. http://dx.doi.org/10.1088/1742-6596/1004/1/012018.

Full text

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!