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Journal articles on the topic 'Okapi bm25'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 February 2022

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1

Tjandra, Ellysa, and Monica Widiasri. "Sistem Repositori Tugas Akhir Mahasiswa dengan Fungsi Peringkat Okapi BM25." Journal of Information Systems Engineering and Business Intelligence 2, no. 2 (2016): 88. http://dx.doi.org/10.20473/jisebi.2.2.88-94.

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Abstrak— Saat ini Jurusan Teknik Informatika Universitas ’X’ mewajibkan mahasiswa yang telah selesai tugas akhir untuk mengumpulkan hasil karya mereka dalam bentuk softcopy (CD) yang berisi program aplikasi dan dokumentasi, serta hardcopy (dalam bentuk buku laporan dan jurnal). Karya tersebut disimpan di perpustakaan secara fisik dan beberapa data disimpan di Digital Library Universitas ’X’. Namun keterbatasan sistem yang ada saat ini menyebabkan kesulitan pencarian hasil karya tugas akhir, karena teknik/metode yang digunakan untuk melakukan pencarian dibuat dalam bentuk query sederhana dengan
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2

Whissell, John S., and Charles L. A. Clarke. "Improving document clustering using Okapi BM25 feature weighting." Information Retrieval 14, no. 5 (2011): 466–87. http://dx.doi.org/10.1007/s10791-011-9163-y.

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3

Tinega, Gesare Asnath, Prof Waweru Mwangi, and Dr Richard Rimiru. "Text Mining in Digital Libraries using OKAPI BM25 Model." International Journal of Computer Applications Technology and Research 7, no. 10 (2018): 398–406. http://dx.doi.org/10.7753/ijcatr0710.1003.

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4

Lee, Yong-Hun, and Sang-Bum Lee. "A Research on Enhancement of Text Categorization Performance by using Okapi BM25 Word Weight Method." Journal of the Korea Academia-Industrial cooperation Society 11, no. 12 (2010): 5089–96. http://dx.doi.org/10.5762/kais.2010.11.12.5089.

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5

Ventura, Juan Antonio Lossio, Clement Jonquet, Mathieu Roche, and Maguelonne Teisseire. "Towards a Mixed Approach to Extract Biomedical Terms from Text Corpus." International Journal of Knowledge Discovery in Bioinformatics 4, no. 1 (2014): 1–15. http://dx.doi.org/10.4018/ijkdb.2014010101.

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The objective of this paper is to present a methodology to extract and rank automatically biomedical terms from free text. The authors present new extraction methods taking into account linguistic patterns specialized for the biomedical domain, statistic term extraction measures such as C-value and statistic keyword extraction measures such as Okapi BM25, and TFIDF. These measures are combined in order to improve the extraction process and the authors investigate which combinations are the more relevant associated to different contexts. Experimental results show that an appropriate harmonic me
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6

Widiasri, Monica, Ellysa Tjandra, and Lisa Maria Chandra. "Peningkatan Kinerja Pencarian Dokumen Tugas Akhir Menggunakan Porter Stemmer Bahasa Indonesia dan Fungsi Peringkat Okapi BM25." Teknika 6, no. 1 (2017): 54–60. http://dx.doi.org/10.34148/teknika.v6i1.65.

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Proses pencarian dokumen yang menggunakan information retrieval akan menerima query dan mengembalikan dokumen yang relevan dengan query pencarian tersebut. Relevansi diperhitungkan dari relevansi kata pada query dan kumpulan dokumen yang dicari. Pada sistem pencarian yang tidak mempertimbangkan variasi morfologi kata mengakibatkan dokumen yang mempunyai kata yang merupakan variasi dari kata pada query tidak dianggap sebagai dokumen hasil pencarian. Proses stemming dilakukan untuk mengenali variasi morfologi tersebut, dengan cara melakukan perubahan pada kata-kata berimbuhan dengan cara penghap
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7

Singh, Iknoor, Carolina Scarton, and Kalina Bontcheva. "Multistage BiCross encoder for multilingual access to COVID-19 health information." PLOS ONE 16, no. 9 (2021): e0256874. http://dx.doi.org/10.1371/journal.pone.0256874.

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The Coronavirus (COVID-19) pandemic has led to a rapidly growing ‘infodemic’ of health information online. This has motivated the need for accurate semantic search and retrieval of reliable COVID-19 information across millions of documents, in multiple languages. To address this challenge, this paper proposes a novel high precision and high recall neural Multistage BiCross encoder approach. It is a sequential three-stage ranking pipeline which uses the Okapi BM25 retrieval algorithm and transformer-based bi-encoder and cross-encoder to effectively rank the documents with respect to the given q
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8

Al-Dallal, Ammar, and Rasha S. Abdul-Wahab. "GA on IR." International Journal of Artificial Life Research 3, no. 2 (2012): 1–14. http://dx.doi.org/10.4018/jalr.2012040101.

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Increasing the growth rates of websites’ number has led to the challenge of assisting Web customers in finding appropriate details from the Internet using an intelligent search engine. Information retrieval (IR) is an essential and useful strategy for Web users; thus, different strategies and techniques are designed for such purpose. Currently, the focus on the usefulness of Artificial Intelligence (AI) has been improved with IR. One AI area is Evolutionary Computation (EC), which is based on designs of natural selection. A traditional and important strategy in EC is Genetic Algorithm (GA); th
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9

Dahir, Sarah, Abderrahim El Qadi, and Hamid Bennis. "Health Query Expansion based on Graph Matching between DBpedia and UMLS." International Journal of Online and Biomedical Engineering (iJOE) 17, no. 06 (2021): 110. http://dx.doi.org/10.3991/ijoe.v17i06.22755.

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<p class="0abstract">Information Retrieval (IR) in the medical domain is considered as a challenging task for many reasons. Short health queries tend to lack information on user's intent, and the target corpus may not have sufficient information for Relevance Feedbacks. And even, if the user obtains relevant documents to his/her queries, it is difficult for him/her to understand the technical terms. In contrast, in this paper, we propose an approach for health queries reformulation based on graph matching between two external linked data sources: DBpedia and Unified Medical Language Syst
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10

Pande Made Risky Cahya Dinatha and Nur Aini Rakhmawati. "Komparasi Term Weighting dan Word Embedding pada Klasifikasi Tweet Pemerintah Daerah." Jurnal Nasional Teknik Elektro dan Teknologi Informasi 9, no. 2 (2020): 155–61. http://dx.doi.org/10.22146/jnteti.v9i2.90.

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Munculnya media sosial mendorong pemerintah untuk memanfaatkan media sosial sebagai sarana penyebaran informasi. Informasi yang diberikan haruslah bermanfaat bagi masyarakat dalam rangka meningkatkan hubungan government to citizen. Klasifikasi terhadap unggahan media sosial pemerintah daerah dapat dilakukan untuk mengetahui jenis informasi yang diunggah. Penelitian klasifikasi unggahan media sosial pada studi kasus pemerintah daerah di Indonesia telah berhasil dilakukan, tetapi pengolahan teks untuk membangun model klasifikasinya masih dapat dieksplorasi. Metode pengolahan teks yang dibahas di
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11

Al-Dallal, Ammar, Rasha S. Abdulwahab, and Ramzi El-Haddadeh. "IR with and without GA." International Journal of Applied Metaheuristic Computing 4, no. 1 (2013): 1–20. http://dx.doi.org/10.4018/jamc.2013010101.

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This paper proposes two IR approaches; the first is IR with GA, which is a GA-based IR approach. This approach introduces modified GA operators that allow IR with GA to achieve high performance. The second IR model is IR without GA, which is based on traditional IR approach. Both enhance the precision and recall of the web search by improving the document representation where an enhanced inverted index is developed for this purpose. Moreover, these two models use the same proposed evaluation function for measuring the document relativity to the user query. A number of experiments were conducte
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12

Babić, Karlo, Francesco Guerra, Sanda Martinčić-Ipšić, and Ana Meštrović. "A Comparison of Approaches for Measuring the Semantic Similarity of Short Texts Based on Word Embeddings." Journal of information and organizational sciences 44, no. 2 (2020): 231–46. http://dx.doi.org/10.31341/jios.44.2.2.

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Measuring the semantic similarity of texts has a vital role in various tasks from the field of natural language processing. In this paper, we describe a set of experiments we carried out to evaluate and compare the performance of different approaches for measuring the semantic similarity of short texts. We perform a comparison of four models based on word embeddings: two variants of Word2Vec (one based on Word2Vec trained on a specific dataset and the second extending it with embeddings of word senses), FastText, and TF-IDF. Since these models provide word vectors, we experiment with various m
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13

Damayanti, Putri, Diana Purwitasari, and Nanik Suciati. "Eliminasi Non-Topic Menggunakan Pemodelan Topik untuk Peringkasan Otomatis Data Tweet dengan Konteks Covid-19." Jurnal Teknologi Informasi dan Ilmu Komputer 8, no. 1 (2021): 199. http://dx.doi.org/10.25126/jtiik.0814324.

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<p>Akun <em>twitter</em>, seperti Suara Surabaya, dapat membantu menyebarkan informasi tentang COVID-19 meskipun ada bahasan lainnya seperti kecelakaan, kemacetan atau topik lain. Peringkasan teks dapat diimplementasikan pada kasus pembacaan data <em>twitter</em> karena banyaknya jumlah <em>tweet</em> yang tersedia, sehingga akan mempermudah dalam memperoleh informasi penting terkini terkait COVID-19. Jumlah variasi bahasan pada teks <em>tweet</em> mengakibatkan hasil ringkasan yang kurang baik. Oleh karena itu dibutuhkan adanya eliminasi &
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14

Godavarthi, Deepthi, and Mary Sowjanya A. "Queries related to COVID-19: a more effective retrieval through finetuned ALBERT with BM25L question answering system." World Journal of Engineering ahead-of-print, ahead-of-print (2021). http://dx.doi.org/10.1108/wje-01-2021-0059.

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Purpose The purpose of this paper is to build a better question answering (QA) system that can furnish more improved retrieval of answers related to COVID-19 queries from the COVID-19 open research data set (CORD-19). As CORD-19 has an up-to-date collection of coronavirus literature, text mining approaches can be successfully used to retrieve answers pertaining to all coronavirus-related questions. The existing a lite BERT for self-supervised learning of language representations (ALBERT) model is finetuned for retrieving all COVID relevant information to scientific questions posed by the medic
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15

Agustina, Meilina, Yufiz Azhar, and Nur Hayatin. "Sistem Perekomendasi Dosen Pembimbing berdasarkan Relevansi Topik Tugas Akhir menggunakan Metode Okapi BM25." Jurnal Repositor 2, no. 9 (2020). http://dx.doi.org/10.22219/repositor.v2i9.672.

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AbstrakSistem rekomendasi adalah sebuah perangkat lunak untuk memberikan rekomendasi kepada pengguna mengenai produk yang dapat digunakannya. Masalah administrasi di kantor jurusan Pendidikan Guru Sekolah Dasar Universitas Muhammadiyah Malang merupakan salah satu permasalahan yang selalu dihadapi oleh para staf TU dan part timer. Penggunaan sistem manual yang masih berjalan saat ini dinilai kurang efektif terhadap waktu, tempat, dan tenaga sehingga diperlukan adanya bantuan berupa sistem informasi. Pada perancangan sistem informasi ini akan menggunakan metode Okapi BM25 dimana metode ini merup
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16

Aklouche, Billel, Ibrahim Bounhas, and Yahya Slimani. "A discriminative method for global query expansion and term reweighting using co-occurrence graphs." Journal of Information Science, March 29, 2021, 016555152199804. http://dx.doi.org/10.1177/0165551521998047.

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This article presents a new query expansion (QE) method aiming to tackle term mismatch in information retrieval (IR). Previous research showed that selecting good expansion terms which do not hurt retrieval effectiveness remains an open and challenging research question. Our method investigates how global statistics of term co-occurrence can be used effectively to enhance expansion term selection and reweighting. Indeed, we build a co-occurrence graph using a context window approach over the entire collection, thus adopting a global QE approach. Then, we employ a semantic similarity measure in
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