Natural language technology and query expansion: issues, state-of-the-art and perspectives

The availability of an abundance of knowledge sources has spurred a large amount of effort in the development and enhancement of Information Retrieval techniques. Users’ information needs are expressed in natural language and successful retrieval is very much dependent on the effective communication of the intended purpose. Natural language queries consist of multiple linguistic features which serve to represent the intended search goal. Linguistic characteristics that cause semantic ambiguity and misinterpretation of queries as well as additional factors such as the lack of familiarity with the search environment affect the users’ ability to accurately represent their information needs, coined by the concept “intention gap”. The latter directly affects the relevance of the returned search results which may not be to the users’ satisfaction and therefore is a major issue impacting the effectiveness of information retrieval systems. Central to our discussion is the identification of the significant constituents that characterize the query intent and their enrichment through the addition of meaningful terms, phrases or even latent representations, either manually or automatically to capture their intended meaning. Specifically, we discuss techniques to achieve the enrichment and in particular those utilizing the information gathered from statistical processing of term dependencies within a document corpus or from external knowledge sources such as ontologies. We lay down the anatomy of a generic linguistic based query expansion framework and propose its module-based decomposition, covering topical issues from query processing, information retrieval, computational linguistics and ontology engineering. For each of the modules we review state-of-the-art solutions in the literature categorized and analyzed under the light of the techniques used.     

Knowledge information processing language: ShapeUp

A new logic programming language, ShapeUp, is developed. ShapeUp is an expanded Prolog system with string matching facilities. The language has been developed to give programmers a new computer programming environment, especially for knowledge information processing. This area includes natural language comprehension and intelligent text processing systems with better man-machine interfaces. For this kind of application, character string data play a principal part rather than conventional numerical data. In ShapeUp, string patterns are introduced as Prolog ‘terms’. Their matching process is performed inside the unification. Thus, a program is far simpler and easier to write and read in ShapeUp, than in conventional Prolog systems, and program size is extremely reduced.     

PPL: A whole-image processing language

This paper presents the design and implementation of the picture processing language (PPL) that extends the syntax and semantics of traditional image processing libraries. PPL provides a rich set of features to support the development of imaging systems. A main aspect is that many of these features treat a whole-image as an individual operand. An efficient memory management scheme is included that allows “in-place operation” with high memory efficiency.The PPL compiler together with an interpreter can work in two modes. The PPL compiler can convert the source code into C files that can be used as macros within a client program. The program can also be executed at run-time by an interpreter. The dual-execution modes make it possible to be used by both imaging researchers and equipment developers.The extended set of PPL instructions can communicate with digital sensors and 3D displays, and store image data into databases across the Internet. The wavelet-based reverse prediction algorithm can speed up the image loading process approximately three times faster than JPEG. The application programming interface (API) of PPL provides all the building blocks for programmers.     

Urdu language processing: a survey

Extensive work has been done on different activities of natural language processing for Western languages as compared to its Eastern counterparts particularly South Asian Languages. Western languages are termed as resource-rich languages. Core linguistic resources e.g. corpora, WordNet, dictionaries, gazetteers and associated tools being developed for Western languages are customarily available. Most South Asian Languages are low resource languages e.g. Urdu is a South Asian Language, which is among the widely spoken languages of sub-continent. Due to resources scarcity not enough work has been conducted for Urdu. The core objective of this paper is to present a survey regarding different linguistic resources that exist for Urdu language processing, to highlight different tasks in Urdu language processing and to discuss different state of the art available techniques. Conclusively, this paper attempts to describe in detail the recent increase in interest and progress made in Urdu language processing research. Initially, the available datasets for Urdu language are discussed. Characteristic, resource sharing between Hindi and Urdu, orthography, and morphology of Urdu language are provided. The aspects of the pre-processing activities such as stop words removal, Diacritics removal, Normalization and Stemming are illustrated. A review of state of the art research for the tasks such as Tokenization, Sentence Boundary Detection, Part of Speech tagging, Named Entity Recognition, Parsing and development of WordNet tasks are discussed. In addition, impact of ULP on application areas, such as, Information Retrieval, Classification and plagiarism detection is investigated. Finally, open issues and future directions for this new and dynamic area of research are provided. The goal of this paper is to organize the ULP work in a way that it can provide a platform for ULP research activities in future.     

Vector C: A vector processing language

The language Vector C is a superset of the conventional (scalar) programming language C with extensions to facilitate vector processing. The design goals and a methodology for performing language extensions and the extended language features of Vector C are presented. The implementation of Vector C on the Cyber 205 is nearing completion. Some empirical data are presented which demonstrate that Vector C can generate a code which executes at speeds that meet or exceed those of equivalent statements from 205 Vector Forum. Readers are assumed to have some knowledge of the C language.     

Natural language processing: a prolog perspective

Natural language processing (NLP) is a vibrant field of interdisciplinary Computer Science research. Ultimately, NLP seeks to build intelligence into software so that software will be able to process a natural language as skillfully and artfully as humans. Prolog, a general purpose logic programming language, has been used extensively to develop NLP applications or components thereof. This report is concerned with introducing the interested reader to the broad field of NLP with respect to NLP applications that are built in Prolog or from Prolog components.     

River: an intermediate language for stream processing

This paper presents both a calculus for stream processing, named Brooklet, and its realization as an intermediate language, named River. Because River is based on Brooklet, it has a formal semantics that enables reasoning about the correctness of source translations and optimizations. River builds on Brooklet by addressing the real‐world details that the calculus elides. We evaluated our system by implementing front‐ends for three streaming languages, and three important optimizations, and a back‐end for the System S distributed streaming runtime. Overall, we significantly lower the barrier to entry for new stream‐processing languages and thus grow the ecosystem of this crucial style of programming. Copyright © 2015 John Wiley & Sons, Ltd.     

Algebraic tools for language processing

A language space provides a unified framework to deal with the properties of language constructs by associating them with their specification rules. The concrete syntax is represented by segments of the language space. The semantics is given by derived operations of the algebras where these constructs are interpreted by the processing tools operating on the language space. We examine in this paper only processing tools that collect syntactic information over the language space. Tools involved in semantics processing such as translators and interpreters are also integrated in the language space but are not discussed here.     

The current programming language standards scene XII: Metalanguages

Developments in the standisation of the syntactic metalanguages during the period January 1980 to May 1983 are reviewed.     

Natural language processing for Nepali text: a review

Because of the proliferation of Nepali textual documents online, researchers in Nepal and overseas have started working towards its automated analysis for quick inferences, using different machine learning (ML) algorithms, ranging from traditional ML-based algorithms to recent deep learning (DL)-based algorithms. However, researchers are still unaware about the recent trends of NLP research direction in the Nepali language. In this paper, we survey different natural language processing (NLP) research works with associated resources in Nepali language. Furthermore, we organize the NLP approaches, techniques, and application tasks used in the Nepali language processing using the comprehensive taxonomy for each of them. Finally, we discuss and analyze based on such assimilated information for further improvement in NLP research works in the Nepali language. Our thorough survey bestows the detailed backgrounds and motivations to researchers, which not only opens up new potential avenues but also ushers towards further progress of NLP research works in the Nepali language.

     

Palimpsest: A layered language for exploratory image processing

Palimpsest is a novel purely-visual language intended to support exploratory live programming. It demonstrates a new paradigm for the visual representation of constraint programming that may be appropriate to future generations of keyboardless and touchscreen devices. The current application domain is that of creative image manipulation, although the paradigm can support a wider range of computational expression. The combination of constraint semantics expressed via a novel image-layering metaphor provides a new approach to supporting a gradual slope of abstraction from direct manipulation to behaviour specification. Exploratory evaluations with a range of users give an indication of likely audiences, and opportunities for future development and application.     

Turbo expert: A knowledge representation and processing language

Turbo Expert, a knowledge representation and processing language, is the basic support language for expert system construction. Turbo Expert has been implemented for IBM PC and for El'brus multiprocessor systems.Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 149–157, September–October, 1991.     

The current programming language standards scene III: COBOL

Developments in the standardisation of COBOL during the period January 1980 to May 1983 are reviewed.     

The current programming language standards scene X: Graphics

Developments in the standardisation of graphics handling in computer systems during the period January 1980 to May 1983 are reviewed.     

The current programming language standards scene VI: BASIC

Developments in the standardisation of BASIC during the period January 1980 to May 1983 are reviewed.     

The current programming language standards scene XIVA: APL

Developments in the standardisation of APL during the period January 1980 to May 1983 are reviewed.     

A review of current state-of-the-art control methods for lower-limb powered prostheses

Lower-limb prostheses aim to restore ambulatory function for individuals with lower-limb amputations. While the design of lower-limb prostheses is important, this paper focuses on the complementary challenge—the control of lower-limb prostheses. Specifically, we focus on powered prostheses, a subset of lower-limb prostheses, which utilize actuators to inject mechanical power into the walking gait of a human user.In this paper, we present a review of existing control strategies for lower-limb powered prostheses, including the control objectives, sensing capabilities, and control methodologies. We separate the various control methods into three main tiers of prosthesis control: High-level control for task and gait phase estimation, mid-level control for desired torque computation (both with and without the use of reference trajectories), and low-level control for enforcing the computed torque commands on the prosthesis. In particular, we focus on the high- and mid-level control approaches in this review. Additionally, we outline existing methods for customizing the prosthetic behavior for individual human users. Finally, we conclude with a discussion on future research directions for powered lower-limb prostheses based on the potential of current control methods and open problems in the field.     

The use of natural language processing in computer-assisted language instruction

This article describes the natural language processing techniques used in two computer-assisted language instruction programs: VERBCON and PARSER. VERBCON is a template-type program which teaches students how to use English verb forms in written texts. In the exercises verbs have been put into the infinitive, and students are required to supply appropriate verb forms. PARSER is intended to help students learn English sentence structure. Using a lexicon and production rules, it generates sentences and asks students to identify their grammatical parts. The article contends that only by incorporating natural language processing techniques can these programs offer a substantial number of exercises and at the same time provide students with informative feedback. Alan Bailin is director of the Effective Writing Program at the University of Western Ontario, London, Ontario, Canada. Philip Thomson is a programmer in the Faculty of Medecine, University of Western Ontario.