Automatic Labeling of Semantic Roles [PDF]
We present a system for identifying the semantic relationships, or semantic roles, filled by constituents of a sentence within a semantic frame. Given an input sentence and a target word and frame, the system labels constituents with either abstract semantic roles, such as Agent or Patient, or more domain-specific semantic roles, such as Speaker ...
Daniel Gildea, Daniel Jurafsky
doaj +5 more sources
A Toolbox and Crowdsourcing Platform for Automatic Labeling of Independent Components in Electroencephalography [PDF]
Independent Component Analysis (ICA) is a conventional approach to exclude non-brain signals such as eye movements and muscle artifacts from electroencephalography (EEG).
Gurgen Soghoyan +11 more
doaj +4 more sources
Combining Differential Kinematics and Optical Flow for Automatic Labeling of Continuum Robots in Minimally Invasive Surgery [PDF]
The segmentation of continuum robots in medical images can be of interest for analyzing surgical procedures or for controlling them. However, the automatic segmentation of continuous and flexible shapes is not an easy task.
BenoƮt Rosa +2 more
doaj +3 more sources
Research on automatic labeling of imbalanced texts of customer complaints based on text enhancement and layer-by-layer semantic matching [PDF]
Due to its potential impact on business efficiency, automated customer complaint labeling and classification are of great importance for management decision making and business applications. The majority of the current research on automated labeling uses
Xiaobo Tang +3 more
doaj +2 more sources
Iktishaf+: A Big Data Tool with Automatic Labeling for Road Traffic Social Sensing and Event Detection Using Distributed Machine Learning [PDF]
Digital societies could be characterized by their increasing desire to express themselves and interact with others. This is being realized through digital platforms such as social media that have increasingly become convenient and inexpensive sensors ...
Ebtesam Alomari +4 more
doaj +2 more sources
TLATR: Automatic Topic Labeling Using Automatic (Domain-Specific) Term Recognition
Topic modeling is a probabilistic graphical model for discovering latent topics in text corpora by using multinomial distributions of topics over words. Topic labeling is used to assign meaningful labels for the discovered topics.
Ciprian-Octavian Truica +1 more
doaj +3 more sources
Automatic Generation of Topic Labels [PDF]
Topic modelling is a popular unsupervised method for identifying the underlying themes in document collections that has many applications in information retrieval. A topic is usually represented by a list of terms ranked by their probability but, since these can be difficult to interpret, various approaches have been developed to assign descriptive ...
Alokaili, A., Aletras, N., Stevenson, M.
openaire +3 more sources
Although deep learning-based fruit detection techniques are becoming popular, they require a large number of labeled datasets to support model training. Moreover, the manual labeling process is time-consuming and labor-intensive.
Wenli Zhang +4 more
doaj +1 more source
Effective Free-Driving Region Detection for Mobile Robots by Uncertainty Estimation Using RGB-D Data
Accurate segmentation of drivable areas and road obstacles is critical for autonomous mobile robots to navigate safely in indoor and outdoor environments.
Toan-Khoa Nguyen +3 more
doaj +1 more source
A Comparative Study of Multi-Label Classification for Document Labeling in Ethical Protocol Review
An ethical clearance document ensures that the research will protect the subject in accordance with existing ethical principles. The ethical clearance is issued by the Research Ethics Commission (KEP).
Rizka Wakhidatus Sholikah +2 more
doaj +1 more source

