Results 61 to 70 of about 356,474 (267)
In recent years, social media messaging app data has served as a precious resource to extract useful information, such as critical clues and evidence in legal trials and criminal investigations.
Seungwook Lee, Youngjoong Ko
doaj +1 more source
Global Relation Embedding for Relation Extraction
We study the problem of textual relation embedding with distant supervision. To combat the wrong labeling problem of distant supervision, we propose to embed textual relations with global statistics of relations, i.e., the co-occurrence statistics of ...
Gur, Izzeddin +5 more
core +1 more source
BioRel: towards large-scale biomedical relation extraction
Background Although biomedical publications and literature are growing rapidly, there still lacks structured knowledge that can be easily processed by computer programs.
Rui Xing, Jie Luo, Tengwei Song
doaj +1 more source
Agricultural Named Entity Recognition Based on Semantic Aggregation and Model Distillation
With the development of smart agriculture, automatic question and answer (Q&A) of agricultural knowledge is needed to improve the efficiency of agricultural information acquisition.
LI Liangde +4 more
doaj +1 more source
We propose a Long Short-Term Memory (LSTM) with attention mechanism to classify psychological stress from self-conducted interview transcriptions.
Fung, Pascale +2 more
core +1 more source
Jointly Embedding Entities and Text with Distant Supervision [PDF]
12 pages; Accepted to 3rd Workshop on Representation Learning for NLP (Repl4NLP 2018).
Newman-Griffis, D. +2 more
openaire +3 more sources
ABSTRACT Background Families of children with cancer experience significant financial strain, even with universal healthcare. Indirect costs, such as productivity losses and non‐medical expenses, are rarely included in economic evaluations, and little is known about how effectively financial aid programmes alleviate this burden. Childhood brain tumours
Megumi Lim +8 more
wiley +1 more source
Same but Different: Distant Supervision for Predicting and Understanding Entity Linking Difficulty
Entity Linking (EL) is the task of automatically identifying entity mentions in a piece of text and resolving them to a corresponding entity in a reference knowledge base like Wikipedia.
Brasoveanu Adrian +7 more
core +1 more source
In situ molecular organization and heterogeneity of the Legionella Dot/Icm T4SS
We present a nearly complete in situ model of the Legionella Dot/Icm type IV secretion system, revealing its central secretion channel and identifying new components. Using cryo‐electron tomography with AI‐based modeling, our work highlights the structure, variability, and mechanism of this complex nanomachine, advancing understanding of bacterial ...
Przemysław Dutka +11 more
wiley +1 more source
Improved Distant Supervised Model in Tibetan Relation Extraction Using ELMo and Attention
The task of relation extraction is classifying the relations between two entities in a sentence. Distant supervision relation extraction can automatically align entities in texts based on Knowledge Base without labeled training data.
Yuan Sun +4 more
doaj +1 more source

