Relevant bibliographies by topics / Okapi bm25

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  1. Journal articles
  2. Dissertations / Theses
  3. Conference papers

Academic literature on the topic 'Okapi bm25'

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

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Journal articles on the topic "Okapi bm25"

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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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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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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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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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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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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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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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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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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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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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Dissertations / Theses on the topic "Okapi bm25"

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Eriksen, Martin. "Rocchio, Ide, Okapi och BIM : En komparativ studie av fyra metoder för relevance feedback." Thesis, Högskolan i Borås, Institutionen Biblioteks- och informationsvetenskap / Bibliotekshögskolan, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-18877.

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This thesis compares four relevance feedback methods. The Rocchio and Ide dec-hi algorithms for the vector space model and the binary independence model and Okapi BM25 within the probabilistic framework. This is done in a custom-made Information Retrieval system utilizing a collection containing 131 896 LA-Times articles which is part of the TREC ad-hoc collection. The methods are compared on two grounds, using only the relevance information from the 20 highest ranked documents from an initial search and also by using all available relevance information. Although a significant effect of choice
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LaBouve, Eric. "Relevance Analysis for Document Retrieval." DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/1976.

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Document retrieval systems recover documents from a dataset and order them according to their perceived relevance to a user’s search query. This is a difficult task for machines to accomplish because there exists a semantic gap between the meaning of the terms in a user’s literal query and a user’s true intentions. Even with this ambiguity that arises with a lack of context, users still expect that the set of documents returned by a search engine is both highly relevant to their query and properly ordered. The focus of this thesis is on document retrieval systems that explore methods of ordering
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Conference papers on the topic "Okapi bm25"

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Champclaux, Yaël, Taoufiq Dkaki, and Josiane Mothe. "ENHANCING HIGH PRECISION BY COMBINING OKAPI BM25 WITH STRUCTURAL SIMILARITY IN AN INFORMATION RETRIEVAL SYSTEM." In 11th International Conference on Enterprise Information Systems. SCITEPRESS - Science and Technology Publications, 2009. http://dx.doi.org/10.5220/0002017202790285.

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Journal articles
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