標(biāo)題: Titlebook: Computational Linguistics and Intelligent Text Processing; 19th International C Alexander Gelbukh Conference proceedings 2023 Springer Natu [打印本頁] 作者: 是英寸 時(shí)間: 2025-3-21 19:26
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: Fraudulent 時(shí)間: 2025-3-21 21:02
https://doi.org/10.1007/978-3-663-04447-5ecessarily correspond to any dictionary senses of the word. To overcome this, we propose a method to find new sense embeddings with known meaning. We term this method refitting, as the new embedding is fitted to model the meaning of a target word in an example sentence. The new lexically refitted em作者: plasma 時(shí)間: 2025-3-22 02:46
https://doi.org/10.1007/978-3-663-04447-5nformation on the web. In many previous studies, human raters check the concordance between text content and evidence-based practice guidelines in order to evaluate information accuracy and completeness. However, human rating cannot be a practical solution, particularly when there is an extremely la作者: 一再困擾 時(shí)間: 2025-3-22 05:37 作者: Grasping 時(shí)間: 2025-3-22 12:00 作者: cuticle 時(shí)間: 2025-3-22 12:56
https://doi.org/10.1007/978-3-663-04532-8Recurrent neural network (RNN) language models are the state-of-the-art language models, but they are notorious for their large size and computation cost. A main source of parameters and computation of RNN language models is embedding matrices. In this paper, we propose a sparse representation-based作者: cuticle 時(shí)間: 2025-3-22 19:44 作者: 拋棄的貨物 時(shí)間: 2025-3-22 22:29
,Str?mungstechnische Grundlagen,detection of suicidal intentions of Tunisians through Facebook. Indeed, among our major contributions we can cite: First, the usage of the Facebook social network due to its popularity in Tunisia required the development of a Facebook application to extract data, we also added some components to ach作者: NIP 時(shí)間: 2025-3-23 04:37 作者: MEAN 時(shí)間: 2025-3-23 06:56 作者: enchant 時(shí)間: 2025-3-23 10:40 作者: 好色 時(shí)間: 2025-3-23 16:37
,Abkürzungen und Formelzeichen,od called . to learn emoji-based representations of resource-poor languages by jointly training them with resource-rich languages using a siamese network..CESNA model consists of twin Bi-directional Long Short-Term Memory Recurrent Neural Networks (Bi-LSTM RNN) with shared parameters joined by a con作者: 招人嫉妒 時(shí)間: 2025-3-23 18:40 作者: 描述 時(shí)間: 2025-3-23 22:57 作者: 可用 時(shí)間: 2025-3-24 03:13
https://doi.org/10.1007/978-3-663-07321-5e, in this paper we identify the contents and sentiments in images through the fusion of both image and text features. We leverage on the fact that AlexNet is a pre-trained model with great performance in image classification and the corresponding set of images are extracted from the web. In particu作者: Euphonious 時(shí)間: 2025-3-24 07:25
https://doi.org/10.1007/978-3-663-07321-5f the major contribution it could make to real applications. The current study focuses on far-field speech emotion recognition using the state-of-the-art spontaneous IEMOCAP emotional data. For classification, a method based on deep convolutional neural networks (DCNN) and extremely randomized trees作者: Tremor 時(shí)間: 2025-3-24 12:02
https://doi.org/10.1007/978-3-663-04448-2, and syntactic structure identification by means of both intrinsic and extrinsic evaluation methods. For such, we use in this work well-known metric for parser evaluation such as bracket cross, leaf ancestor for intrinsic evaluation, as well as the application of such parsers to the task of noun ph作者: 斗志 時(shí)間: 2025-3-24 15:14
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/232601.jpg作者: LAST 時(shí)間: 2025-3-24 21:16 作者: 杠桿支點(diǎn) 時(shí)間: 2025-3-25 02:23 作者: 商店街 時(shí)間: 2025-3-25 07:24 作者: deficiency 時(shí)間: 2025-3-25 10:44 作者: 諂媚于性 時(shí)間: 2025-3-25 14:15
0302-9743 raction, Lexical resources, Machine translation, Morphology, syntax, Semantics and text similarity, Sentiment analysis, Syntax and parsing, Text categorization and clustering, Text generation, and? Text mining. .978-3-031-23803-1978-3-031-23804-8Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: otic-capsule 時(shí)間: 2025-3-25 18:48 作者: Sinus-Node 時(shí)間: 2025-3-26 00:02 作者: 拘留 時(shí)間: 2025-3-26 01:52
,Grundlagen der Str?mungsmaschinen,elated with email opens and outperforms words from the standard ANEW lexicon and other state of the art affective lexica. Implications of this findings can be incorporated into writing tools to improve the productivity of marketing campaigns.作者: 真繁榮 時(shí)間: 2025-3-26 08:09
https://doi.org/10.1007/978-3-642-94859-6t corpus, having 2,575 sentences, part of the UAIC Romanian Dependency Treebank, a balanced corpus that contains especially non-standard Romanian language. Finally, we have made graphs to analyse the relations and sentiments of communicators from the Chat corpus.作者: 放肆的我 時(shí)間: 2025-3-26 09:07
https://doi.org/10.1007/978-3-662-10112-4eviews centered on subjects like movies, music, etc., this work is the first of its kind. We also provide several insights from the collated embeddings, thus helping users gain a better understanding of their options as well as select companies using customized preferences.作者: FRET 時(shí)間: 2025-3-26 15:43
https://doi.org/10.1007/978-3-662-10112-4opics (Trump/Brexit) that are generating a lot of discussion and debate on Twitter. We chose the political domain given the power that Social Media has on possibly influencing voters (.) and the ‘strong’ opinions that are expressed in this area.作者: 保守 時(shí)間: 2025-3-26 17:46
https://doi.org/10.1007/978-3-663-07321-5ures. Lastly, to combine the image and text predictions we propose a novel sentiment score. Our model is evaluated on Twitter dataset of images and corresponding labels and tweets. We show that accuracy by merging scores from text and image models is higher than using any one system alone.作者: 原始 時(shí)間: 2025-3-26 21:28
https://doi.org/10.1007/978-3-663-07321-5ng clean data. In the case of PLDA and SVM classifiers, the classification rates were significantly decreased. To further improve the performance of far-field speech emotion recognition, a method based on multi-style training is proposed, which results in significant improvements in the classification rates.作者: mutineer 時(shí)間: 2025-3-27 02:18 作者: ectropion 時(shí)間: 2025-3-27 07:35
Detection of?Change in?the?Senses of?AI in?Popular Discourseifferent significations according to different cultural contexts. Our aim in this paper is to study the semantic shifts in the meaning of AI in different contexts by examining the mapping of the words to different semantic vector spaces over time.作者: Cardiac 時(shí)間: 2025-3-27 09:43 作者: anus928 時(shí)間: 2025-3-27 16:28 作者: 搖曳 時(shí)間: 2025-3-27 20:15 作者: Graphite 時(shí)間: 2025-3-28 01:16 作者: 領(lǐng)袖氣質(zhì) 時(shí)間: 2025-3-28 03:19 作者: SLUMP 時(shí)間: 2025-3-28 07:41 作者: Medley 時(shí)間: 2025-3-28 10:56 作者: Infantry 時(shí)間: 2025-3-28 14:39
Detection of Suicidal Intentions of Tunisians via Facebooke set of the most relevant attributes in identification of suicidal ideation especially among Tunisians. We reached encouraging results after a number of classification experiments thanks to an empirical comparison of the obtained performances by several subsets of features.作者: 意外 時(shí)間: 2025-3-28 22:48 作者: neutral-posture 時(shí)間: 2025-3-29 01:45
Sentiment Analysis of?Code-Mixed Languages Leveraging Resource Rich Languageses to a common sentiment space. Also, we introduce a basic clustering based preprocessing method to capture variations of code-mixed transliterated words. Our experiments reveal that SACMT outperforms the state-of-the-art approaches in sentiment analysis for code-mixed text by 7.6% in accuracy and 10.1% in F-score.作者: Kernel 時(shí)間: 2025-3-29 03:41
Cross-Framework Evaluation for?Portuguese POS Taggers and?Parsersrase identification, for extrinsic evaluation. The comparison proposed in this work takes into account the different linguistic theories and frameworks each parser subscribes to, but it is not dependent of any particular one.作者: Gratuitous 時(shí)間: 2025-3-29 09:40 作者: 懶洋洋 時(shí)間: 2025-3-29 14:00
https://doi.org/10.1007/978-3-663-04532-8 method to compress embedding matrices and reduce both the size and computation of the models. We conduct experiments on the PTB dataset and also test its performance on cellphones to illustrate its effectiveness.作者: 開花期女 時(shí)間: 2025-3-29 17:15
https://doi.org/10.1007/978-3-642-94859-6es to a common sentiment space. Also, we introduce a basic clustering based preprocessing method to capture variations of code-mixed transliterated words. Our experiments reveal that SACMT outperforms the state-of-the-art approaches in sentiment analysis for code-mixed text by 7.6% in accuracy and 10.1% in F-score.作者: 驚呼 時(shí)間: 2025-3-29 19:46 作者: 草率女 時(shí)間: 2025-3-30 00:17 作者: aspersion 時(shí)間: 2025-3-30 04:36
Using Shallow Semantic Analysis to?Implement Automated Quality Assessment of?Web Health Care Informanformation on the web. In many previous studies, human raters check the concordance between text content and evidence-based practice guidelines in order to evaluate information accuracy and completeness. However, human rating cannot be a practical solution, particularly when there is an extremely la作者: 飲料 時(shí)間: 2025-3-30 11:48 作者: prodrome 時(shí)間: 2025-3-30 13:01 作者: 怒目而視 時(shí)間: 2025-3-30 20:01
Sparse Word Representation for?RNN Language Models on?CellphonesRecurrent neural network (RNN) language models are the state-of-the-art language models, but they are notorious for their large size and computation cost. A main source of parameters and computation of RNN language models is embedding matrices. In this paper, we propose a sparse representation-based作者: 在前面 時(shí)間: 2025-3-30 22:36
Predicting Email Opens with?Domain-Sensitive Affect Detectionuage processing. We demonstrate the advantages of incorporating domain information for affect analysis, and subsequently for the prediction of user responses to marketing emails. Emails are a primary form of marketing communication, and email subject lines are the only indicators of whether the rece作者: 險(xiǎn)代理人 時(shí)間: 2025-3-31 01:11
Detection of Suicidal Intentions of Tunisians via Facebookdetection of suicidal intentions of Tunisians through Facebook. Indeed, among our major contributions we can cite: First, the usage of the Facebook social network due to its popularity in Tunisia required the development of a Facebook application to extract data, we also added some components to ach作者: agglomerate 時(shí)間: 2025-3-31 06:53
Relationships and Sentiment Analysis of Fictional or Real Characterslly annotated corpus, the Romanian version of the novel . by Henryk Sinkiewicz. The NodeXL program can draw graphs of character relationships, to analyse relationships both in the fictional and the real-world. In this research, we describe how we have refined our tool, which becomes both a detector 作者: 斑駁 時(shí)間: 2025-3-31 12:42
