Towards Improving Causality Mining using BERT with Multi-level Feature Networks
نویسندگان
چکیده
منابع مشابه
Improving Event Causality Recognition with Multiple Background Knowledge Sources Using Multi-Column Convolutional Neural Networks
We propose a method for recognizing such event causalities as “smoke cigarettes” → “die of lung cancer” using background knowledge taken from web texts as well as original sentences from which candidates for the causalities were extracted. We retrieve texts related to our event causality candidates from four billion web pages by three distinct methods, including a why-question answering system,...
متن کاملImproving Feature Level Likelihoods using Cloud Features
The performance of many computer vision methods depends on the quality of the local features extracted from the images. For most methods the local features are extracted independently of the task and they remain constant through the whole process. To make features more dynamic and give models a choice in the features they can use, this work introduces a set of intermediate features referred as ...
متن کاملTowards constructing an Integrative, Multi-Level Model for Cognition: The Function of Semantic Networks
Integrated approaches try to connect different constructs in different theories and reinterpret them using a common conceptual framework. In this research, using the concept of processing levels, an integrated, three-level model of the cognitive systems has been proposed and evaluated. Processing levels are divided into three categories of Feature-Oriented, Semantic and Conceptual Level based o...
متن کاملMining Multi-Level Rules with Recurrent Items Using FP-Tree
Association rule mining has received broad research in the academic and wide application in the real world. As a result, many variations exist and one such variant is the mining of multi-level rules. The mining of multi-level rules has proved to be useful in discovering important knowledge that conventional algorithms such as Apriori, SETM, DIC etc., miss. However, existing techniques for minin...
متن کاملMulti-Level and Multi-Scale Feature Aggregation Using Sample-level Deep Convolutional Neural Networks for Music Classification
Music tag words that describe music audio by text have different levels of abstraction. Taking this issue into account, we propose a music classification approach that aggregates multilevel and multi-scale features using pre-trained feature extractors. In particular, the feature extractors are trained in sample-level deep convolutional neural networks using raw waveforms. We show that this appr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Ksii Transactions on Internet and Information Systems
سال: 2022
ISSN: ['1976-7277', '2288-1468']
DOI: https://doi.org/10.3837/tiis.2022.10.002