CKIP Lab

Chinese Knowledge and Information Processing

CKIP Lab

The CKIP (Chinese Knowledge and Information Processing) group is a research team formed by the Institute of Information Science and the Institute of Linguistics of Academia Sinica in 1986. Its purpose is to establish a fundamental research environment for Chinese natural language processing. The preliminary goal of the project was to construct research infrastructures with reusable resources that could be shared by domestic and international research institutes. The accomplished resources include Chinese electronic dictionaries, Mandarin Chinese corpora, and processing technologies for Chinese texts. With these environments and technologies now well established, we are focusing on knowledge-based information processing. This area of research is motivated by the flood of information on the WWW for which effective and autonomous information processing tools are still lacking. To achieve high-level intelligent information processing, many of the most challenging research problems in the areas of knowledge acquisition, knowledge representation, and knowledge utilization are currently being addressed.

Join Us

We are looking for full-time research assistants. .

We are looking for full-time software engineer. .

News

Jun 2024 Our research paper — “Generating Attractive and Authentic Copywriting from Customer Reviews” has been accepted by “NAACL 2024”.
Jun 2024 Our research paper — “Plug-in Language Model: Controlling Text Generation with a Simple Regression Model” has been accepted by “NAACL 2024 Findings”.
Mar 2024 Our research paper — “Automatic Construction of a Chinese Review Dataset for Aspect Sentiment Triplet Extraction via Iterative Weak Supervision” has been accepted by “LREC-Coling 2024”.
Nov 2022 Our research paper — “HanTrans: An Empirical Study on Cross-Era Transferability of Chinese Pre-trained Language Model” has been accepted by “ROCLING 2022”.
Jun 2022 Our research paper — “Converting the Sinica Treebank of Mandarin Chinese to Universal Dependencies” has been accepted by “LREC Workshop on LAW”.

Research Areas

Deep Learning

Deep Learning

Deep learning architectures such as deep neural networks, deep belief networks, recurrent neural networks and convolutional neural networks have been applied to fields including computer vision, speech recognition, natural language processing, audio recogn……

Knowledge Representation

Knowledge Representation

On knowledge representation area, we focus on the basic theory of knowledge ontology structure and the representation models for meticulous semantics. By analysis the nuance of synonyms, we found the representation method for meticulous semantics, and know……

Language Processing

Language Processing

We focus on concept-centric Chinese processing technology. The developed technology uses the statistics, language grammar, and common sense information obtained by automatic extraction as the basic knowledge to analyze the conceptual structure of the file ……

Knowledge Extraction

Knowledge Extraction

We research on how to automatically extract language knowledge and common sense. We expect that the language processing technology and the acquired knowledge can automatically analyze a large amount of text in the Internet and extract knowledge from it. Kn……

Chatter Bot

Chatter Bot

Chatter Bots are computer programs that talk via dialogue or text. They can simulate human conversation and pass the Turing test. Chatbots can be used for practical purposes, such as customer service or information acquisition. Some chatbots are equipped w……