Abstract Using text question and answer technology to improve the efficiency of judicial personnel in process case handling can greatly reduce labour costs. This paper proposes a hybrid neural network model that combines pre-training BERT Bi-GRU. The first uses learn powerful semantic capabilities, then Bi-GRU information between question, finally gets corresponding legal text. experimental res...

This paper introduces an Intelligent Computer Assisted Language Learning system designed to provide reading input for language learners based on the syntactic complexity of their language production. The system analyzes the linguistic complexity of texts produced by the user and of texts in a pedagogic target language corpus to identify texts that are well-suited to foster acquisition. These te...

Instructional texts consist of sequences of instructions designed in order to reach an objective. The author or the generator of instructional texts must follow a number of principles to guarantee that the text is of any use. Similarly, a user must follow step by step the instructions in order to reach the results expected. In this paper, we explore facets of instructional texts: general protot...

The paper presents a new type of nonlinear discourse structure found to be very common in free English texts. This structure reeects nonlinear presentation of the information and knowledge conveyed by the texts. It is argued that such nonlinearity is representationally and informationally advantageous because it allows one to create smaller, more compact texts. The paper presents a heuristics-b...

Text mining deals with complex and unstructured texts. Usually a particular collection of texts that is specified to one or more domains is necessary. We have developed a customizable text classifier for users to mine the collection automatically. It derives from the sentence category of the HNC theory and corresponding techniques. It can start with a few texts, and it can adjust automatically ...

We present the thesaurus-based indexing technology developed by the Center for Information Research under the Information System RUSSIA project. The technology is based on using basic properties of coherent text. Initially the technology was applied for automatic processing of Russian official (government) texts. Currently the instrument is adapted to process English texts for TREC-6 routing task.

This paper describes the development of a prototype document retrieval system based on frequency calculations and corpora comparison techniques. The prototype, WILDER, generated simple frequency information based on which calculations of document relevance could be made. The prototype was built to allow the University of Surrey to debut in the U.S. Text Retrieval Competition (TREC). User querie...

We investigate the automatic identification of negated and speculative statements in biomedical texts, focusing on the clinical domain. Our goal is to evaluate the performance of simple, Regex-based algorithms that have the advantage of low computational cost, simple implementation, and do not rely on the accurate computation of deep linguistic features of idiosyncratic clinical texts. The perf...