Results 281 to 290 of about 218,873 (322)

Automatically Extracting Form Labels

2008 IEEE 24th International Conference on Data Engineering, 2008
We describe a machine-learning-based approach for extracting attribute labels from Web form interfaces. Having these labels is a requirement for several techniques that attempt to retrieve and integrate data that reside in online databases and that are hidden behind form interfaces, including schema matching and clustering, and hidden-Web crawlers ...
Hoa Nguyen, Eun Yong Kang, Juliana Freire   +2 more
openaire   +1 more source

Automatic labeling hierarchical topics

Proceedings of the 21st ACM international conference on Information and knowledge management, 2012
Recently, statistical topic modeling has been widely applied in text mining and knowledge management due to its powerful ability. A topic, as a probability distribution over words, is usually difficult to be understood. A common, major challenge in applying such topic models to other knowledge management problem is to accurately interpret the meaning ...
Xianling Mao, Zhaoyan Ming, Zheng-Jun Zha, Tat-Seng Chua, Hongfei Yan, Xiaoming Li 0001   +5 more
openaire   +1 more source

Automatic Class Labeling for CiteSeerX

2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2013
The CiteSeerx project at the University of Arkansas uses a browsing interface is based on the Association for Computing Machinery's Computing Classification System (ACM CCS). CCS contains just 369 categories whereas the CiteSeerx database contains over 2 million documents.
Surya Dhairya Kashireddy, Susan Gauch, Syed Masum Billah   +2 more
openaire   +1 more source

Automatically Labelled Software Topic Model

International Journal of Open Source Software and Processes, 2020
Public software repositories (SR) maintain a massive amount of valuable data offering opportunities to support software engineering (SE) tasks. Researchers have applied information retrieval techniques in mining software repositories. Topic models are one of these techniques.
Youcef Bouziane, Mustapha Kamel Abdi, Salah Sadou   +2 more
openaire   +1 more source

Automatic segmentation and labeling of speech

[Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing, 1991
The authors investigate an automatic approach to segmentation of labeled speech and labeling and segmentation of speech when only the orthographic transcription of speech is available. The technique is based on a phone recognition system based on a trigram phonotactic model, gamma distribution phone duration models, and a spectral model based on five ...
Andrej Ljolje, Michael Riley 0001
openaire   +1 more source

Automatic Labeling for Hierarchical Topics with NETL

2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2020
Hierarchical topic model is the method used in considering topics with hierarchical relationships. Neural embedding topic labelling (NETL) is a method utilized to label topics with neural embedding, even though it labels topics without topic relationships. The labels of hierarchical topics should have hierarchical relationship with other labels.
Rinto Kozono, Ryosuke Saga
openaire   +1 more source

Semi-Automatically Labeling Objects in Images

IEEE Transactions on Image Processing, 2009
Labeling objects in images plays a crucial role in many visual learning and recognition applications that need training data, such as image retrieval, object detection and recognition. Manually creating object labels in images is time consuming and, thus, becomes impossible for labeling a large image dataset.
Wen Wu, Jie Yang 0001
openaire   +2 more sources

A UNIFIED APPROACH TO AUTOMATIC LABEL PLACEMENT

International Journal of Computational Geometry & Applications, 2003
The automatic placement of text or symbol labels corresponding to graphical features is critical in several application areas such as cartography, geographical information systems, and graph drawing. In this paper we present a general framework for solving the problem of assigning text or symbol labels to a set of graphical features in two dimensional
Konstantinos G. Kakoulis, Ioannis G. Tollis   +1 more
openaire   +3 more sources

Automatic labelling of documents based on ontology

2015 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM), 2015
Recently cloud systems have been spread widely through internet so that we can get to huge amount of complex information (mainly in text) easily and quickly. However we can hardly catch up with the changes inside since we should go through them and see quickly what's going on. This is why automatic labelling is indispensable.
Naoya Okumura, Takao Miura
openaire   +1 more source

Automatic labeling of multinomial topic models

Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, 2007
Multinomial distributions over words are frequently used to model topics in text collections. A common, major challenge in applying all such topic models to any text mining problem is to label a multinomial topic model accurately so that a user can interpret the discovered topic. So far, such labels have been generated manually in a subjective way.
Qiaozhu Mei, Xuehua Shen, ChengXiang Zhai   +2 more
openaire   +1 more source