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Titlebook: Computational Linguistics and IntelligentText Processing; 20th International C Alexander Gelbukh Conference proceedings 2023 Springer Natur

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樓主: DUCT
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發(fā)表于 2025-3-23 11:49:58 | 只看該作者
12#
發(fā)表于 2025-3-23 14:07:58 | 只看該作者
Fusing Phonetic Features and?Chinese Character Representation for?Sentiment Analysisons. We are the first to argue that these two important properties can play a major role in Chinese sentiment analysis. Hence, we learn phonetic features of Chinese characters and fuse them with their textual and visual features in order to mimic the way humans read and understand Chinese text. Expe
13#
發(fā)表于 2025-3-23 21:30:56 | 只看該作者
Sentiment-Aware Recommendation System for?Healthcare Using Social Mediaeby seeking guidance and interacting with people of the community. The shared content, though informal and unstructured in nature, contains valuable medical and/or health related information and can be leveraged to produce structured suggestions to the common people. In this paper, at first we propo
14#
發(fā)表于 2025-3-23 23:27:19 | 只看該作者
Sentiment Analysis Through Finite State Automatand the subjectivity of the user generated contents make the automatic “understanding” of texts extremely hard. Assuming that the semantic orientation of sentences is based on the manipulation of sentiment words, we built from scratch, for the Italian language, a network of local grammars for the ann
15#
發(fā)表于 2025-3-24 03:53:22 | 只看該作者
16#
發(fā)表于 2025-3-24 10:35:36 | 只看該作者
Opinion Spam Detection with?Attention-Based LSTM Networksake online reviews, can be detrimental to both customers as well as organizations. Several methods have been proposed to automatically detect fake opinions; however, the majority of these methods focus on feature learning techniques based on a large number of handcrafted features. Deep learning and
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發(fā)表于 2025-3-24 11:53:54 | 只看該作者
18#
發(fā)表于 2025-3-24 16:02:27 | 只看該作者
,Grundzüge turbulenter Str?mungen,ut not sufficient to cover all elements of verb structure. We conducted a statistical analysis of semantic role representation in VerbNet and FrameNet to provide empirical evidence of insufficiency. The consequence of that is a hybrid role-scalar approach.
19#
發(fā)表于 2025-3-24 19:47:01 | 只看該作者
https://doi.org/10.1007/978-3-031-24340-0Computer Science; Informatics; Conference Proceedings; Research; Applications
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發(fā)表于 2025-3-24 23:22:46 | 只看該作者
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