Profiling and Evolution of Intellectual Property
Not on the map. Why?
Abstract (arXiv)
In recent years, with the rapid growth of Internet data, the number and types of scientific and technological resources are also rapidly expanding. However, the increase in the number and category of information data will also increase the cost of information acquisition. For technology-based enterprises or users, in addition to general papers, patents, and other resources, policies related to technology or the development of their industries should also belong to a type of scientific and technological resource. Extracting valuable science and technology policy resources from a huge amount of mixed-content data and providing accurate and fast retrieval will help break down information barriers and reduce information-acquisition costs, which has profound social significance and utility. This article focuses on the difficulties and problems in the field of science and technology policy and introduces related technologies and developments.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 15 of its 63 references that are in the map. First posted on arXiv 20 Apr 2022.
Builds on
15 of 63 references.
References · 15
- 2015Character-level Convolutional Networks for Text Classificationcited by 2,293
- 2014Convolutional Neural Networks for Sentence Classificationcited by 1,124
- 2016Bag of Tricks for Efficient Text Classificationcited by 869
- 2018Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Networkcited by 415
- 2018Graph Convolutional Networks for Text Classificationcited by 345
- 2018Universality of Deep Convolutional Neural Networkscited by 176
- 2016Recurrent Neural Network for Text Classification with Multi-Task Learningcited by 144
- 2022Filter-enhanced MLP is All You Need for Sequential Recommendationcited by 96
- 2015Convolutional Neural Network Architectures for Matching Natural Language Sentencescited by 82
- 2016Text Matching as Image Recognitioncited by 59
- 2021Self-Supervised Graph Co-Training for Session-based Recommendationcited by 43
- 2021Identity-Aware CycleGAN for Face Photo-Sketch Synthesis and Recognitioncited by 39
3 more
- 2018Entity-Duet Neural Ranking: Understanding the Role of Knowledge Graph Semantics in Neural Information Retrievalcited by 33
- 2015A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representationscited by 32
- 2019Deep Collaborative Filtering with Multi-Aspect Information in Heterogeneous Networkscited by 27
Built on by
Not cited yet.