Natural Notation for the Domestic Internet of Things

This study explores the use of natural language to give instructions that might be interpreted by Internet of Things (IoT) devices in a domestic `smart home' environment. We start from the proposition that reminders can be considered as a type of end-user programming, in which the executed actions might be performed either by an automated agent or by the author of the reminder. We conducted an experiment in which people wrote sticky notes specifying future actions in their home. In different conditions, these notes were addressed to themselves, to others, or to a computer agent.We analyse the linguistic features and strategies that are used to achieve these tasks, including the use of graphical resources as an informal visual language. The findings provide a basis for design guidance related to end-user development for the Internet of Things.Comment: Proceedings of the 5th International symposium on End-User Development (IS-EUD), Madrid, Spain, May, 201

Bayesian Information Extraction Network

Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs are applicable to probabilistic language modeling. To demonstrate the potential of DBNs for natural language processing, we employ a DBN in an information extraction task. We show how to assemble wealth of emerging linguistic instruments for shallow parsing, syntactic and semantic tagging, morphological decomposition, named entity recognition etc. in order to incrementally build a robust information extraction system. Our method outperforms previously published results on an established benchmark domain.Comment: 6 page

Linguistic Analysis of Natural Language Engineering Requirements

In engineering design, the needs of the customer are expressed through engineering requirement statements. These requirement statements are often expressed using natural language because they are easily created and read. However, there are several problems associated with natural language requirements including but not limited to ambiguity, incompleteness, understandability, testability and over specificity. Several representation and analysis tools have been proposed to address these problems within a requirement statement. These tools include formal languages, such as UML and SysML, requirement management tools, such as IBM Telelogic Doors, and natural language processors such as QuARS. These tools assist in the systematic elicitation and creation of requirements, improve requirement visibility and traceability, and provide a central repository for shared access. However, these tools do not prescribe a formal representation of a requirement and its elements. The effectiveness of these tools can be greatly improved with a formalized syntax for expressing engineering requirements. The research presented in this thesis examines engineering requirements from a linguistic viewpoint and leads to a formalized syntax based on parts of speech, grammatical functions, and sentence structure. Specifically, a requirement statement is decomposed into four syntactical elements: artifact, necessity, function, and condition. Further, grammar and linguistics provide the basis for requirements classification into functional or non-functional and qualitative or quantitative requirements. Finally, the deficiencies in current natural language requirements such as incompleteness, understandability, ambiguity, and specificity, are identified through the formal syntax and grammatical rules. The requirements syntax and analysis method are demonstrated on 110 requirements from the Family of Medium Tactical Vehicles (FMTV). Using the syntax and analysis method proposed, the count of incomplete requirements, percentages of function and non-functional requirements, and specificity of the requirement statements in the document were determined. Identifying such requirement measures will help to improve the expressiveness of requirement statements and help to identify if appropriate requirements are being authored for the different stages of design (i.e. conceptual, embodiment, detailed). To further improve the analysis method proposed, more quality attributes of requirement statements have to be addressed such as ambiguity and traceability. The end goal is to develop a syntax and analysis method that addresses all quality attributes of a requirement statement that is not empirically based but rule based

A DSL for PIM specifications: design and attribute grammar based implementation

IIS*Case is a model driven software tool that provides information system modeling and prototype generation. It comprises visual and repository based tools for creating various platform independent model (PIM) specifications that are latter transformed into the other, platform specific specifications, and finally to executable programs. Apart from having PIMs stored as repository definitions, we need to have their equivalent representation in the form of a domain specific language. One of the main reasons for this is to allow for checking the formal correctness of PIMs being created. In the paper, we present such a meta-language, named IIS*CDesLang. IIS*CDesLang is specified by an attribute grammar (AG), created under a visual programming environment for AG specifications, named VisualLIS

An Ontological Analysis of Use Case Modeling Grammar

Use case modeling is a popular technique for representing the functional requirements of an information system. The simple graphical notation of use case diagrams, accompanied by well-structured narrative descriptions, makes use case models fairly easy to read and understand. This simplicity, however, belies the challenges associated with creating use case models. There is little, if any, theory underlying use cases, and little more than loose guidelines for creating a complete, consistent, and integrated set of use cases. We argue that there is a need for more rigor and consistency in the grammatical constructs used in use case modeling. Toward this end, we present a theoretically- and practice-based assessment of use case modeling constructs, and make recommendations for future research to improve and strengthen this technique

Generating Abstractive Summaries from Meeting Transcripts

Summaries of meetings are very important as they convey the essential content of discussions in a concise form. Generally, it is time consuming to read and understand the whole documents. Therefore, summaries play an important role as the readers are interested in only the important context of discussions. In this work, we address the task of meeting document summarization. Automatic summarization systems on meeting conversations developed so far have been primarily extractive, resulting in unacceptable summaries that are hard to read. The extracted utterances contain disfluencies that affect the quality of the extractive summaries. To make summaries much more readable, we propose an approach to generating abstractive summaries by fusing important content from several utterances. We first separate meeting transcripts into various topic segments, and then identify the important utterances in each segment using a supervised learning approach. The important utterances are then combined together to generate a one-sentence summary. In the text generation step, the dependency parses of the utterances in each segment are combined together to create a directed graph. The most informative and well-formed sub-graph obtained by integer linear programming (ILP) is selected to generate a one-sentence summary for each topic segment. The ILP formulation reduces disfluencies by leveraging grammatical relations that are more prominent in non-conversational style of text, and therefore generates summaries that is comparable to human-written abstractive summaries. Experimental results show that our method can generate more informative summaries than the baselines. In addition, readability assessments by human judges as well as log-likelihood estimates obtained from the dependency parser show that our generated summaries are significantly readable and well-formed.Comment: 10 pages, Proceedings of the 2015 ACM Symposium on Document Engineering, DocEng' 201