標(biāo)題: Titlebook: Computational Linguistics and Intelligent Text Processing; 15th International C Alexander Gelbukh Conference proceedings 2014 Springer-Verl [打印本頁] 作者: 傳家寶 時間: 2025-3-21 17:22
書目名稱Computational Linguistics and Intelligent Text Processing影響因子(影響力)
書目名稱Computational Linguistics and Intelligent Text Processing影響因子(影響力)學(xué)科排名
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書目名稱Computational Linguistics and Intelligent Text Processing被引頻次
書目名稱Computational Linguistics and Intelligent Text Processing被引頻次學(xué)科排名
書目名稱Computational Linguistics and Intelligent Text Processing年度引用
書目名稱Computational Linguistics and Intelligent Text Processing年度引用學(xué)科排名
書目名稱Computational Linguistics and Intelligent Text Processing讀者反饋
書目名稱Computational Linguistics and Intelligent Text Processing讀者反饋學(xué)科排名
作者: Brain-Imaging 時間: 2025-3-21 23:36
https://doi.org/10.1007/978-3-642-54906-9clustering and classification; document management and text processing; information retrieval; informat作者: ERUPT 時間: 2025-3-22 00:32 作者: 漂亮 時間: 2025-3-22 05:57
https://doi.org/10.1007/978-3-030-37285-9 of time, record all written or spoken input, and compare this data to the corpus in question. As this is not very practical, we suggest here a more indirect way to do this. Previous work suggests that people’s word associations can be derived from corpus statistics. These word associations are know作者: Negligible 時間: 2025-3-22 11:51
Kayleigh O’Donnell,Amy L. Reschlyproduces and implements the main components of Optimality Theory. However, we formulate the hypothesis that some of its limitations are mainly due to a poor representation of the constraints used. Finally, we show how a better representation of the constraints used would yield better results.作者: addict 時間: 2025-3-22 16:20
Lisa M. Hagermoser Sanetti,Hao-Jan Luhlications. However, lexical resources which provide information about such classes are only available for a handful of worlds languages. Because manual development of such resources is extremely time consuming and cannot reliably capture domain variation in classification, methods for automatic indu作者: addict 時間: 2025-3-22 19:22
https://doi.org/10.1007/978-3-030-37285-9ed scope without considering the benefits of including domain knowledge to a general ontology. Furthermore, most existing resources lack meta-information about association strength (weights) and annotations (frequency information like ., . ... or relevance information like . or .). In this paper, we作者: Popcorn 時間: 2025-3-22 22:42 作者: Aromatic 時間: 2025-3-23 04:17 作者: flex336 時間: 2025-3-23 09:29
https://doi.org/10.1007/978-981-97-0558-0lysis tools and resources. Social media posts, especially those made by the younger generation, are usually written using colloquial Arabic and include a lot of slang, many of which evolves over time. While some work has been carried out to build modern standard Arabic sentiment lexicons, these need作者: 無瑕疵 時間: 2025-3-23 10:13 作者: 健談 時間: 2025-3-23 14:37 作者: violate 時間: 2025-3-23 20:51
The Hong Kong Polytechnic Universityr understanding of text and helps to significantly increase the accuracy of many text mining tasks. Concept extraction from text is a key step in concept-level text analysis. In this paper, we propose a ConceptNet-based semantic parser that deconstructs natural language text into concepts based on t作者: 面包屑 時間: 2025-3-24 02:01
https://doi.org/10.1007/978-3-319-46034-5s learning methods only utilize homo-lingual corpus. Inspired by transfer learning, we propose a novel language transfer method to obtain word embeddings via language transfer. Under this method, in order to obtain word embeddings of one language (target language), we train models on corpus of anoth作者: extrovert 時間: 2025-3-24 06:16 作者: Metamorphosis 時間: 2025-3-24 06:44
Student Engagement in Neoliberal Timesrd may present different signatures in different contexts, i.e. polysemous words can be used with different senses in different contexts. Intuitively, disambiguating word senses for topic models can enhance their discriminative capabilities. In this work, we propose a joint model to automatically in作者: 表狀態(tài) 時間: 2025-3-24 11:20 作者: 殺人 時間: 2025-3-24 17:58
https://doi.org/10.1007/978-981-10-3200-4for morphological segmentation from a computational linguistics point of view. We survey morphological segmentation methods covering methods based on MDL (minimum description length), MLE (maximum likelihood estimation), MAP (maximum a posteriori), parametric and non-parametric Bayesian approaches. 作者: BUCK 時間: 2025-3-24 20:17 作者: 過份好問 時間: 2025-3-25 00:17
Towards a Critical Curriculum for Engagementn from developers. One of such under-resourced languages is Kafi-noonoo which is spoken in the south-western regions of Ethiopia. This paper presents the development of part-of-speech tagger for Kafi-noonoo. In order to develop the tagger, we employed a hybrid of two systems: statistical and rule-ba作者: 擁護(hù)者 時間: 2025-3-25 03:53
https://doi.org/10.1007/978-3-319-05567-1nizer. Identification and classification of chemical entities are relatively more complex and challenging compared to the other related tasks. As chemical entities we focus on IUPAC and IUPAC related entities. The algorithm performs feature selection within the framework of a robust machine learning作者: 我還要背著他 時間: 2025-3-25 07:50 作者: 桶去微染 時間: 2025-3-25 11:57
Computational Linguistics and Intelligent Text Processing978-3-642-54906-9Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 使人入神 時間: 2025-3-25 18:19 作者: 緯線 時間: 2025-3-25 23:31
Student Engagement in Neoliberal Times, there is no computational work available for the language. Finite state morphology is one of the successful approaches applied in a wide variety of languages over the year. Therefore we adapted the finite state approach to analyse morphology of the Bishnupriya Manipuri language.作者: 刺耳 時間: 2025-3-26 02:53 作者: 道學(xué)氣 時間: 2025-3-26 05:18
Morphological Analysis of the Bishnupriya Manipuri Language Using Finite State Transducers, there is no computational work available for the language. Finite state morphology is one of the successful approaches applied in a wide variety of languages over the year. Therefore we adapted the finite state approach to analyse morphology of the Bishnupriya Manipuri language.作者: Ablation 時間: 2025-3-26 10:15 作者: PON 時間: 2025-3-26 13:32
0302-9743 networks; machine translation and multilingualism; information retrieval; text classification and clustering; text summarization; plagiarism detection; style and spelling checking; speech processing; and applications.978-3-642-54905-2978-3-642-54906-9Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Gesture 時間: 2025-3-26 17:45
Lisa M. Hagermoser Sanetti,Hao-Jan Luh those developed for English without language-specific feature engineering. This yields interesting results which line up well with those obtained for other languages, demonstrating the cross-linguistic nature of this type of classification. However, we also discover and discuss issues which require作者: Rebate 時間: 2025-3-27 00:52 作者: 雪上輕舟飛過 時間: 2025-3-27 02:46 作者: surrogate 時間: 2025-3-27 08:33
https://doi.org/10.1007/978-981-97-0558-0g the presented approach to generalize across dialects with some minor modifications. ??Results of experiments, that targeted Egyptian Arabic, show the approach’s ability to detect subjective internet slang represented by single words or by multi-word expressions, as well as classifying the polarity作者: 蝕刻 時間: 2025-3-27 11:35 作者: 情感 時間: 2025-3-27 15:58
Luke K. Fryer,Ronnel B. King,Lily M. Zeng, Apache Tika and Poppler in various configurations. From the output of these tools we recover proper boundaries using on-the-fly language models and language-independent extraction heuristics. In our research, we looked especially at publications from the European Union, which constitute a valuable作者: forthy 時間: 2025-3-27 20:26
https://doi.org/10.1007/978-3-319-05567-1elop many models of CRF using these feature combinations. In order to further improve the performance the outputs of these classifiers are combined together using a classifier ensemble technique based on modified DE. Our experiments with the benchmark datasets yield the recall, precision and F-measu作者: GUILT 時間: 2025-3-28 01:29
Verb Clustering for Brazilian Portuguese those developed for English without language-specific feature engineering. This yields interesting results which line up well with those obtained for other languages, demonstrating the cross-linguistic nature of this type of classification. However, we also discover and discuss issues which require作者: octogenarian 時間: 2025-3-28 05:13 作者: Grating 時間: 2025-3-28 08:16
Compound?Terms and?Their?Multi-word?Variants: Case?of?German?and?Russian?Languages variation patterns for these two languages and demonstrate that the transformation of a morphological compound into a syntagmatic compound mainly occurs when the term denomination needs to be enlarged.作者: 金絲雀 時間: 2025-3-28 11:29 作者: 不開心 時間: 2025-3-28 15:36
Simple TF·IDF Is Not the Best You Can Get for Regionalism Classificationximizes the discrimination of such terms given a reduced bootstrapping set of examples labeled for each region (400). We present performance examples for the Spanish variations across the Americas and Spain.作者: Jingoism 時間: 2025-3-28 19:44
Improved Text Extraction from PDF Documents for Large-Scale Natural Language Processing, Apache Tika and Poppler in various configurations. From the output of these tools we recover proper boundaries using on-the-fly language models and language-independent extraction heuristics. In our research, we looked especially at publications from the European Union, which constitute a valuable作者: 有惡意 時間: 2025-3-29 01:17
Modified Differential Evolution for Biochemical Name Recognizerelop many models of CRF using these feature combinations. In order to further improve the performance the outputs of these classifiers are combined together using a classifier ensemble technique based on modified DE. Our experiments with the benchmark datasets yield the recall, precision and F-measu作者: 出處 時間: 2025-3-29 06:46 作者: Aesthete 時間: 2025-3-29 10:56
Optimality Theory as a Framework for Lexical Acquisitionproduces and implements the main components of Optimality Theory. However, we formulate the hypothesis that some of its limitations are mainly due to a poor representation of the constraints used. Finally, we show how a better representation of the constraints used would yield better results.作者: judiciousness 時間: 2025-3-29 12:20 作者: 一罵死割除 時間: 2025-3-29 19:38 作者: 具體 時間: 2025-3-29 19:57 作者: 誓言 時間: 2025-3-30 03:21
Compound?Terms and?Their?Multi-word?Variants: Case?of?German?and?Russian?Languagesand syntactic variations which have to be handled by any NLP applications. If the syntactic variations of multi-word terms have been described and tools designed to process them, only a few works studied the syntagmatic variants of compound terms. This paper is dedicated to the identification of suc作者: 出汗 時間: 2025-3-30 05:32 作者: BULLY 時間: 2025-3-30 11:32 作者: Embolic-Stroke 時間: 2025-3-30 13:17
Improved Text Extraction from PDF Documents for Large-Scale Natural Language Processingne of the largest problems in the conversion of PDF documents is the detection of the boundaries of common textual units such as paragraphs, sentences and words. PDF is a file format optimized for printing and encapsulates a complete description of the layout of a document including text, fonts, gra作者: BLANK 時間: 2025-3-30 18:02
Dependency-Based Semantic Parsing for Concept-Level Text Analysisr understanding of text and helps to significantly increase the accuracy of many text mining tasks. Concept extraction from text is a key step in concept-level text analysis. In this paper, we propose a ConceptNet-based semantic parser that deconstructs natural language text into concepts based on t作者: GOAT 時間: 2025-3-31 00:34 作者: 精致 時間: 2025-3-31 01:28
Exploring Applications of Representation Learning in Nepalilabeled Nepali text, we induce clusters of different sizes. The use of these clusters as features significantly improves the performance compared to the baseline on two standard NLP tasks. In a part-of-speech (PoS) tagging experiment where the train and test domain are the same, the accuracy on the 作者: Ibd810 時間: 2025-3-31 08:33
