標(biāo)題: Titlebook: Computational Linguistics and Intelligent Text Processing; 17th International C Alexander Gelbukh Conference proceedings 2018 Springer Inte [打印本頁] 作者: ISH 時(shí)間: 2025-3-21 17:23
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
書目名稱Computational Linguistics and Intelligent Text Processing網(wǎng)絡(luò)公開度
書目名稱Computational Linguistics and Intelligent Text Processing網(wǎng)絡(luò)公開度學(xué)科排名
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: octogenarian 時(shí)間: 2025-3-21 23:33
A Roadmap Towards Machine Intelligenceerties these machines should have, focusing in particular on . and .. We discuss a simple environment that could be used to incrementally teach a machine the basics of natural-language-based communication, as a prerequisite to more complex interaction with human users. We also present some conjectur作者: Torrid 時(shí)間: 2025-3-22 03:20 作者: AXIS 時(shí)間: 2025-3-22 06:51
Persianp: A Persian Text Processing Toolboxprovides fundamental Persian text processing steps includes several modules. In developing some modules of the toolbox such as normalizer, tokenizer, sentencizer, stop word detector, and Part-Of-Speech tagger previous studies are applied. In other modules i.e. Persian lemmatizer and NP chunker, new 作者: 松馳 時(shí)間: 2025-3-22 09:38 作者: gene-therapy 時(shí)間: 2025-3-22 16:08 作者: gene-therapy 時(shí)間: 2025-3-22 17:17 作者: 沐浴 時(shí)間: 2025-3-22 23:40
A New Language Model Based on Possibility Theorys paper, we propose a new language modeling approach based on the possibility theory. Our goal is to suggest a method for estimating the possibility of a word-sequence and to test this new approach in a machine translation system. We propose a word-sequence possibilistic measure, which can be estima作者: Fraudulent 時(shí)間: 2025-3-23 04:04
Combining Discrete and Neural Features for Sequence Labelingwith discrete features, neural models have two main advantages. First, they take low-dimensional, real-valued embedding vectors as inputs, which can be trained over large raw data, thereby addressing the issue of feature sparsity in discrete models. Second, deep neural networks can be used to automa作者: Employee 時(shí)間: 2025-3-23 07:52
New Recurrent Neural Network Variants for Sequence Labelingwe compare them to the more traditional RNN architectures of Elman and Jordan. We explain in details the advantages of these new variants of RNNs with respect to Elman’s and Jordan’s RNN. We evaluate all models, either new or traditional, on three different tasks: POS-tagging of the French Treebank,作者: Insulin 時(shí)間: 2025-3-23 12:20
Mining the Web for Collocations: IR Models of Term AssociationsNLP, which feeds into several other tasks (e.g., parsing, idioms, summarization, etc.). Despite this attention the problem has remained a “daunting challenge.” As others have observed before, existing approaches based on frequencies and statistical information have limitations. An even bigger proble作者: instill 時(shí)間: 2025-3-23 14:21 作者: MINT 時(shí)間: 2025-3-23 18:49
Description of Turkish Paraphrase Corpus Structure and Generation Methodexible, multipurpose and expandable. Here we describe the steps we took in the development of Turkish paraphrase corpus, the factors we considered, problems we faced and how we dealt with them. Currently our corpus contains nearly 4000 sentences with the ratio of 60% paraphrase and 40% non-paraphras作者: 臭了生氣 時(shí)間: 2025-3-23 23:44
Extracting Terminological Relationships from Historical Patterns of Social Media Termstweets for example) and then to trace the history of each term. Similar history indicates a relationship between terms. This indication can be validated using further processing. For example, if the term t1 and t2 were frequently used in Twitter at certain days, and there is a match in the frequency作者: Mundane 時(shí)間: 2025-3-24 05:47 作者: Offbeat 時(shí)間: 2025-3-24 08:04 作者: 刺耳 時(shí)間: 2025-3-24 13:15 作者: Culmination 時(shí)間: 2025-3-24 15:20 作者: NUL 時(shí)間: 2025-3-24 20:00
,Die mehrstufigen Str?mungsmaschinen,between these linguistic data formats is impossible since they are increasingly multiplatform and multi-providers. LDF suffer from several communication issues. Therefore, they have to face several interoperability issues in order to guarantee consistency and avoid redundancy. In an interoperability作者: machination 時(shí)間: 2025-3-25 02:00
https://doi.org/10.1007/978-3-662-30213-2provides fundamental Persian text processing steps includes several modules. In developing some modules of the toolbox such as normalizer, tokenizer, sentencizer, stop word detector, and Part-Of-Speech tagger previous studies are applied. In other modules i.e. Persian lemmatizer and NP chunker, new 作者: uncertain 時(shí)間: 2025-3-25 04:54
,Die Kavitations- und überschallgefahr,the simple sum of word embeddings (SOWE). However, very few methods demonstrate the ability to reverse the process – recovering sentences from sentence embeddings. Amongst the many sentence embeddings, SOWE has been shown to maintain semantic meaning, so in this paper we introduce a method for movin作者: 輕快走過 時(shí)間: 2025-3-25 10:56 作者: 話 時(shí)間: 2025-3-25 14:43 作者: BLOT 時(shí)間: 2025-3-25 16:14 作者: OASIS 時(shí)間: 2025-3-25 23:47 作者: Metastasis 時(shí)間: 2025-3-26 02:09 作者: abject 時(shí)間: 2025-3-26 06:08
https://doi.org/10.1007/978-3-8351-9035-1NLP, which feeds into several other tasks (e.g., parsing, idioms, summarization, etc.). Despite this attention the problem has remained a “daunting challenge.” As others have observed before, existing approaches based on frequencies and statistical information have limitations. An even bigger proble作者: BUMP 時(shí)間: 2025-3-26 09:59
https://doi.org/10.1007/978-3-8351-9035-1undamental aspects of the description of the verb: the notion of lexical item and the distinction between arguments and adjuncts. Following up on studies in natural language processing and linguistics, we embrace the double hypothesis (.) of a continuum between ambiguity and vagueness, and (.) of a 作者: 天賦 時(shí)間: 2025-3-26 14:59
https://doi.org/10.1007/978-3-8351-9035-1exible, multipurpose and expandable. Here we describe the steps we took in the development of Turkish paraphrase corpus, the factors we considered, problems we faced and how we dealt with them. Currently our corpus contains nearly 4000 sentences with the ratio of 60% paraphrase and 40% non-paraphras作者: Nebulizer 時(shí)間: 2025-3-26 19:52
Dampfturbinen und Dampfkraftanlagen,tweets for example) and then to trace the history of each term. Similar history indicates a relationship between terms. This indication can be validated using further processing. For example, if the term t1 and t2 were frequently used in Twitter at certain days, and there is a match in the frequency作者: 吞噬 時(shí)間: 2025-3-26 21:24
Hydrodynamische Kupplungen und Wandler,esources for low-resourced languages. We propose to exploit corpora available in several languages for building bilingual and trilingual terminologies. Typically, terminology information extracted in better resourced languages is associated with the corresponding units in lower-resourced languages t作者: 刺耳的聲音 時(shí)間: 2025-3-27 04:59 作者: 獨(dú)特性 時(shí)間: 2025-3-27 06:38
https://doi.org/10.1007/978-3-319-75477-2artificial intelligence; internet; machine translations; natural language processing (NLP); semantic inf作者: 剛開始 時(shí)間: 2025-3-27 09:47
978-3-319-75476-5Springer International Publishing AG, part of Springer Nature 2018作者: 玩忽職守 時(shí)間: 2025-3-27 15:33
,Die mehrstufigen Str?mungsmaschinen, for each data format. With this method, we establish a complex grid between existing data formats allowing the mapping to the unifier using algebraic specification. Then, we apply our approach on Arabic lexical data. We experiment our approach using Specware software.作者: FUSE 時(shí)間: 2025-3-27 17:47 作者: Carcinoma 時(shí)間: 2025-3-27 22:48 作者: 悲痛 時(shí)間: 2025-3-28 05:01 作者: blister 時(shí)間: 2025-3-28 08:42
Conference proceedings 2018ntics, discourse, and dialog...Part II: machine translation and multilingualism; sentiment analysis, opinion mining, subjectivity, and social media; text classification and categorization; information extraction; and applications.?.作者: Incise 時(shí)間: 2025-3-28 12:41
Conference proceedings 20182016. ..The total of 89 papers presented in the two volumes was carefully reviewed and selected from 298 submissions. The book also contains 4 invited papers and a memorial paper on Adam Kilgarriff’s Legacy to Computational Linguistics...The papers are organized in the following topical sections:..P作者: 他日關(guān)稅重重 時(shí)間: 2025-3-28 16:46 作者: 賭博 時(shí)間: 2025-3-28 21:11
Persianp: A Persian Text Processing Toolboxideas in preparing required training data and/or applying new techniques are presented. Experimental results show the strong performance of the toolbox in each part. The accuracies of the tokenizer, the POS tagger, the lemmatizer and the NP chunker are 97%, 95.6%, 97%, 97.2%, respectively.作者: Glycogen 時(shí)間: 2025-3-29 02:03 作者: Cantankerous 時(shí)間: 2025-3-29 04:04 作者: 負(fù)擔(dān) 時(shí)間: 2025-3-29 09:54 作者: 我的巨大 時(shí)間: 2025-3-29 12:29 作者: fledged 時(shí)間: 2025-3-29 18:26 作者: aristocracy 時(shí)間: 2025-3-29 19:48
Hydrodynamische Kupplungen und Wandler,raction varies between 0.454 and 0.966, while the quality of the interlingual relations varies between 0.309 and 0.965. The resource built contains 4,588 medical terms in Ukrainian and their 34,267 relations with French and English terms.作者: 滲入 時(shí)間: 2025-3-29 23:53
A New Language Model Based on Possibility Theoryhe new language model with the probabilistic one used in statistical MT systems. The results, in terms of the METEOR metric, show that the possibilistic-language model is better than the probabilistic one. However, in terms of BLEU and TER scores, the probabilistic model remains better.作者: vascular 時(shí)間: 2025-3-30 05:51
Description of Turkish Paraphrase Corpus Structure and Generation Methodmulated in a database structure integrated with Turkish dictionary. The sources we used till now are news texts from Bilcon 2005 corpus, a set of professionally translated sentence pairs from MSRP corpus, multiple Turkish translations from different languages that are involved in Tatoeba corpus and user generated paraphrases.作者: Abrade 時(shí)間: 2025-3-30 10:04
Adaptation of Cross-Lingual Transfer Methods for the Building of Medical Terminology in Ukrainianraction varies between 0.454 and 0.966, while the quality of the interlingual relations varies between 0.309 and 0.965. The resource built contains 4,588 medical terms in Ukrainian and their 34,267 relations with French and English terms.作者: inspired 時(shí)間: 2025-3-30 14:21
0302-9743 in April 2016. ..The total of 89 papers presented in the two volumes was carefully reviewed and selected from 298 submissions. The book also contains 4 invited papers and a memorial paper on Adam Kilgarriff’s Legacy to Computational Linguistics...The papers are organized in the following topical se
