Search Results - Content Analysis and Indexing- indexing methods. General Terms Algorithms

MergedTrie: Efficient textual indexing by Ferrández, Antonio, Peral, Jesús

“… Typical data structures for textual indexing are Hash Tables and some variants of Tries such as the Double Trie (DT…”
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Soil Quality Indexing Strategies for Evaluating Sugarcane Expansion in Brazil by Cherubin, Maurício R., Karlen, Douglas L., Cerri, Carlos E. P., Franco, André L. C., Tormena, Cássio A., Davies, Christian A., Cerri, Carlos C.

“…: one using principal component analysis (7 indicators) and the other based on expert opinion (5 indicators…”
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Algorithmic indexing in MEDLINE frequently overlooks important concepts and may compromise literature search results by Amar-Zifkin, Alexandre, Ekmekjian, Taline, Paquet, Virginie, Landry, Tara

“…Objective: To evaluate the appropriateness of indexing of algorithmically-indexed MEDLINE records. Methods…”
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Quantitative analysis of culture using millions of digitized books by Michel, Jean-Baptiste, Shen, Yuan Kui, Aiden, Aviva Presser, Veres, Adrian, Gray, Matthew K, Pickett, Joseph P, Hoiberg, Dale, Clancy, Dan, Norvig, Peter, Orwant, Jon, Pinker, Steven, Nowak, Martin A, Aiden, Erez Lieberman

“… Analysis of this corpus enables us to investigate cultural trends quantitatively. We survey the vast terrain of 'culturomics,' focusing on linguistic and cultural phenomena that were reflected in the English language between 1800 and 2000…”
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Biomedical literature classification with a CNNs-based hybrid learning network by Yan, Yan, Yin, Xu-Cheng, Yang, Chun, Li, Sujian, Zhang, Bo-Wen

“… However, few research efforts have addressed semantic indexing with deep learning. The use of semantic indexing in the biomedical literature has been limited for several reasons…”
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Characterization of the mechanism of drug-drug interactions from PubMed using MeSH terms by Lu, Yin, Figler, Bryan, Huang, Hong, Tu, Yi-Cheng, Wang, Ju, Cheng, Feng

“… In this paper, we introduced an automatic computational method for the systematic analysis of the mechanism of DDIs using MeSH…”
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The BioLexicon: a large-scale terminological resource for biomedical text mining by Thompson, Paul, McNaught, John, Montemagni, Simonetta, Calzolari, Nicoletta, del Gratta, Riccardo, Lee, Vivian, Marchi, Simone, Monachini, Monica, Pezik, Piotr, Quochi, Valeria, Rupp, CJ, Sasaki, Yutaka, Venturi, Giulia, Rebholz-Schuhmann, Dietrich, Ananiadou, Sophia

“…Background Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to…”
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Performance Evaluation of Keyword Extraction Methods and Visualization for Student Online Comments by Liu, Feng, Huang, Xiaodi, Huang, Weidong, Duan, Sophia Xiaoxia

“… (particular when it comes to repeatedly delivered subjects). In this paper, we compare the performance of traditional machine learning algorithms and two deep learning…”
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Enriching a biomedical event corpus with meta-knowledge annotation by Thompson, Paul, Nawaz, Raheel, McNaught, John, Ananiadou, Sophia

“…, does an event describe a fact, a hypothesis, an experimental result or an analysis of results…”
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Customer gender prediction system on hierarchical E-commerce data by Khan, Mohammad Masud, Sohrab, Mohammad Golam, Yousuf, Mohammad Abu

“…” from transactional E-commerce data. We introduce different sets of learning algorithms including unique IDs decomposition, context window-based history generation, and extract identical…”
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Information filtering based on corrected redundancy-eliminating mass diffusion by Zhu, Xuzhen, Yang, Yujie, Chen, Guilin, Medo, Matus, Tian, Hui, Cai, Shi-Min

“…, the CRE yields significant improvements in terms of recommendation accuracy and diversity. A detailed analysis is presented to unveil the origins of the observed differences between the CRE and mainstream similarity indices…”
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Thesaurus based automatic keyphrase indexing by Medelyan, Olena, Witten, Ian H.

“…We propose a new method that enhances automatic keyphrase extraction by using semantic information on terms and phrases gleaned from a domain-specific thesaurus…”
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A Hybrid Approach for Short-Term Forecasting of Wind Speed by Tatinati, Sivanagaraja, Veluvolu, Kalyana C.

“…We propose a hybrid method for forecasting the wind speed. The wind speed data is first decomposed into intrinsic mode functions (IMFs…”
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A parametric methodology for text classification by Karanikolas, Nikitas N., Skourlas, Christos

“… to the ‘average class document’ of each class. In both cases we use key phrases (text phrases or key terms…”
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Maximizing Influence Over Streaming Graphs with Query Sequence by Zhao, Yuying, Hu, Yunfei, Yuan, Pingpeng, Jin, Hai

“…Now, with the prevalence of social media, such as Facebook, Weibo, how to maximize influence of individuals, products, actions in new media is of practical…”
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Enhancing web page classification through image-block importance analysis by Fersini, E., Messina, E., Archetti, F.

“… a visual layout analysis. We propose different methods to estimate the visual image-blocks importance, to smooth the term weight according to the importance of the blocks…”
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Applying genetic algorithms to query optimization in document retrieval by Horng, Jorng-Tzong, Yeh, Ching-Chang

“…This paper proposes a novel approach to automatically retrieve keywords and then uses genetic algorithms to adapt the keyword weights…”
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A new enhancement to the R-tree node splitting by Al-Badarneh, Amer F., Yaseen, Qussai, Hmeidi, Ismail

“…The performance of spatial queries depends mainly on the underlying index structure used to handle them. R-tree, a well-known spatial index structure, suffers…”
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Document indexing: a concept-based approach to term weight estimation by Kang, Bo-Yeong, Lee, Sang-Jo

“…Traditional index weighting approaches for information retrieval from texts depend on the term frequency based analysis of the text contents…”
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Classification of microarrays; synergistic effects between normalization, gene selection and machine learning by Önskog, Jenny, Freyhult, Eva, Landfors, Mattias, Rydén, Patrik, Hvidsten, Torgeir R

“… methods with 21 different numbers of selected genes and eight machine learning methods. Performance in term of error rate was rigorously estimated by repeatedly…”
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