Inflection-Tolerant Ontology-Based Named Entity Recognition for Real-Time Applications

A growing number of applications users daily interact with have to operate in (near) real-time: chatbots, digital companions, knowledge work support systems - just to name a few. To perform the services desired by the user, these systems have to analyze user activity logs or explicit user input extremely fast. In particular, text content (e.g. in form of text snippets) needs to be processed in an information extraction task. Regarding the aforementioned temporal requirements, this has to be accomplished in just a few milliseconds, which limits the number of methods that can be applied. Practically, only very fast methods remain, which on the other hand deliver worse results than slower but more sophisticated Natural Language Processing (NLP) pipelines. In this paper, we investigate and propose methods for real-time capable Named Entity Recognition (NER). As a first improvement step, we address word variations induced by inflection, for example present in the German language. Our approach is ontology-based and makes use of several language information sources like Wiktionary. We evaluated it using the German Wikipedia (about 9.4B characters), for which the whole NER process took considerably less than an hour. Since precision and recall are higher than with comparably fast methods, we conclude that the quality gap between high speed methods and sophisticated NLP pipelines can be narrowed a bit more without losing real-time capable runtime performance

Scheme 2003: proceedings of the fourth workshop on scheme and functional programming

technical reportThis report contains the papers presented at the Fourth Workshop on Scheme and Functional Programming. The purpose of the Scheme Workshop is to discuss experience with and future developments of the Scheme programming language?including the future of Scheme standardization?as well as general aspects of computer science loosely centered on the general theme of Scheme

Design, Implementation, Use, and Evaluation of Ox: An Attribute- Grammar Compiling System based on Yacc, Lex, and C

Ox generalizes the function of Yacc in the way that attribute grammars generalize context-free grammars. Ordinary Yacc and Lex specifications may be augmented with definitions of synthesized and inherited attributes written in C syntax. From these specifications, Ox generates a program that builds and decorates attributed parse trees. Ox accepts a most general class of attribute grammars. The user may specify postdecoration traversals for easy ordering of side effects such as code generation. Ox handles the tedious and error-prone details of writing code for parse-tree management, so its use eases problems of security and maintainability associated with that aspect of translator development. The translators generated by Ox use internal memory management that is often much faster than the common technique of calling malloc once for each parse-tree node. Ox is a Yacc/Lex/C preprocessor, and is designed to bring attribute grammars closer to the mainstream of Unix-based language development. Ox inherits all of the familiar syntax and semantics of Yacc, Lex, and C. It is relatively easy to convert programs between Ox code and pure Yacc/Lex/C code. Ox has been used to build a compiler for a small (eighty grammar rules) block-structured imperative programming language. This paper considers Ox\u27s design, implementation, and use, evaluates the performance of Ox-generated evaluators, and makes recommendations for improvements in Ox

The Effects of Foreign Accent and Language on Reaction Time and Accuracy in an Air Traffic Control Task

The present study examines the effect of foreign accent interference with the ability to execute commands presented in speech format. The objective of this study was to demonstrate that a foreign accent influences performance. Participants were between 18 and 40 years of age. Half of the participants were native speakers of Spanish who began learning English as a second language via the classroom setting. The other half were native English-speaking with little or no exposure to the Spanish language. The experimental design was similar to an aviation scenario where participants listened to simulated ATC procedural commands and execute them on a simulated control panel. Response time (in milliseconds) and accuracy were recorded. Accuracy was measure by incorrect responses and false starts. Incorrect responses were measured when participants pressed an arrow key different from the commanded direction. False starts occurred when the participant pressed a key before the command was presented. The results of this study did not reveal an effect of language for reaction time. However, the false start data indicated a significant effect on accent for native English speakers, but not an effect on accent for non-native English speakers. On the contrary, the data from incorrect responses does not show a significant effect of accent for native English speakers but a significant difference in effect of accent on non-native English speakers. Therefore, the accuracy hypotheses were not supported

The design of a neural network compiler

Computer simulation is a flexible and economical way for rapid prototyping and concept evaluation with Neural Network (NN) models. Increasing research on NNs has led to the development of several simulation programs. Not all simulations have the same scope. Some simulations allow only a fixed network model and some are more general. Designing a simulation program for general purpose NN models has become a current trend nowadays because of its flexibility and efficiency. A proper programming language specifically for NN models is preferred since the existing high-level languages such as C are for NN designers from a strong computer background. The program translations for NN languages come from combinations which are either interpreter and/or compiler. There are also various styles of programming languages such as a procedural, functional, descriptive and object-oriented. The main focus of this thesis is to study the feasibility of using a compiler method for the development of a general-purpose simulator - NEUCOMP that compiles the program written as a list of mathematical specifications of the particular NN model and translates it into a chosen target program. The language supported by NEUCOMP is based on a procedural style. Information regarding the list of mathematical statements required by the NN models are written in the program. The mathematical statements used are represented by scalar, vector and matrix assignments. NEUCOMP translates these expressions into actual program loops. NEUCOMP enables compilation of a simulation program written in the NEUCOMP language for any NN model, contains graphical facilities such as portraying the NN architecture and displaying a graph of the result during training and finally to have a program that can run on a parallel shared memory multi-processor system

Vermont Agency of Transportation Employee Retention and Knowledge Management Study

In 2015, the Vermont Agency of Transportation (VTrans) developed a new strategic plan that included five goals that would support the agency’s mission and vision. Goal 5 of the plan is: Develop a workforce to meet the strategic needs of the agency. VTrans leaders were concerned with the loss of employees due to turnover and the subsequent impact of knowledge loss on the operations of the agency. This applied research study used a mixed methods approach in data gathering to help determine the state of employee retention and knowledge management (KM) at VTrans and to provide tools that could help with both retention and KM issues. Key steps in this study involved an organizational assessment of turnover and KM practices at VTrans, a scan of other state DOTs concerning retention and KM practices, and a pilot project to address both issues. With guidance provided by a Technical Advisory Committee (TAC), the decision was made to focus most of the research in specific units of the Highway Division