Results 231 to 240 of about 1,750,538 (276)

Feature selection in text classification

2016 24th Signal Processing and Communication Application Conference (SIU), 2016
In recent years, text classification have been widely used. Dimension of text data has increased more and more. Working of almost all classification algorithms is directly related to dimension. In high dimension data set, working of classification algorithms both takes time and occurs over fitting problem.
Sahin, Durmus Ozkan, Ates, Nurullah, Kilic, Erdal   +2 more
openaire   +2 more sources

Hybrid Model For Text Classification

2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA), 2018
Increasing popularity of social media sites (e.g., Twitter, Facebook) leads to the increasing amount of online data. Student's casual talks on these social media sites can be used to know their educational experiences i.e. their worries, opinions, feelings, and emotions about the learning process. However, the main challenge is to analyze this informal
Priyanka Ingole, Smita Bhoir, A.V. Vidhate   +2 more
openaire   +1 more source

INTELLIGENT NLP-DRIVEN TEXT CLASSIFICATION

International Journal on Artificial Intelligence Tools, 2002
Information Retrieval (IR) and NLP-driven Information Extraction (IE) are complementary activities. IR helps in locating specific documents within a huge search space (localization) while IE supports the localization of specific information within a document (extraction or explanation). In application scenarios both capabilities are usually needed. IE
R. Basili, Moschitti, Alessandro
openaire   +1 more source

Bilingual Text Classification

2007
Bilingual documentation has become a common phenomenon in official institutions and private companies. In this scenario, the categorization of bilingual text is a useful tool. In this paper, different approaches will be proposed to tackle this bilingual classification task.
Jorge Civera, Elsa Cubel, Enrique Vidal
openaire   +1 more source

Text Generation for Imbalanced Text Classification

2019 16th International Joint Conference on Computer Science and Software Engineering (JCSSE), 2019
The problem of imbalanced data can be frequently found in the real-world data. It leads to the bias of classification models, that is, the models predict most samples as major classes which are often the negative class. In this research, text generation techniques were used to generate synthetic minority class samples to make the text dataset balanced.
Suphamongkol Akkaradamrongrat, Pornpimon Kachamas, Sukree Sinthupinyo   +2 more
openaire   +1 more source

Concatenate text embeddings for text classification

2017 International Conference on Internet of Things, Embedded Systems and Communications (IINTEC), 2017
Text embedding has gained a lot of interests in text classification area. This paper investigates the popular neural document embedding method Paragraph Vector as a source of evidence in document ranking. We focus on the effects of combining knowledge-based with knowledge-free document embeddings for text classification task.
Hamid Machhour, Ismail Kassou
openaire   +1 more source

Multilingual Text Classification Using Ontologies

2007
In this paper, we investigate strategies for automatically classifying documents in different languages thematically, geographically or according to other criteria. A novel linguistically motivated text representation scheme is presented that can be used with machine learning algorithms in order to learn classifications from pre-classified examples and
de Melo, G., Siersdorfer, S.
openaire   +2 more sources

Text Classification

2021
Chengqing Zong, Rui Xia, Jiajun Zhang
openaire   +1 more source

Transductive Text Classification

2002
For many practical uses of text classification, it is crucial that the learner be able to generalize well using little training data. A news-filtering service, for example, requiring a hundred days’ worth of training data is unlikely to please even the most patient users.
openaire   +1 more source

Text Classification

Usman Qamar, Muhammad Summair Raza
  +5 more sources