Natural Language Statements Research Articles

Diagnosing behavioral differences between business process models: An approach based on event structures

Companies operating in multiple markets or segments often need to manage multiple variants of the same business process. Such multiplicity may stem for example from distinct products, different types of customers or regulatory differences across countries in which the companies operate. During the management of these processes, analysts need to compare models of multiple process variants in order to identify opportunities for standardization or to understand performance differences across variants. To support this comparison, this paper proposes a technique for diagnosing behavioral differences between process models. Given two process models, it determines if they are behaviorally equivalent, and if not, it describes their differences in terms of behavioral relations – like causal dependencies or conflicts – that hold in one model but not in the other. The technique is based on a translation from process models to event structures, a formalism that describes the behavior as a collection of events (task instances) connected by binary behavioral relations. A naïve version of this translation suffers from two limitations. First, it produces redundant difference statements because an event structure describing a process may contain unnecessary event duplications. Second, this translation is not directly applicable to process models with cycles as the corresponding event structure is infinite. To tackle the first issue, the paper proposes a technique for reducing the number of events in an event structure while preserving the behavior. For the second issue, relying on the theory of complete unfolding prefixes, the paper shows how to construct a finite prefix of the unfolding of a possibly cyclic process model where all possible causes of every activity is represented. Additionally, activities that can occur multiple times in an execution of the process are distinguished from those that can occur at most once. The finite prefix thus enables the diagnosis of behavioral differences in terms of activity repetition and causal relations that hold in one model but not in the other. The method is implemented as a prototype that takes as input process models in the Business Process Model and Notation (BPMN) and produces difference statements in natural language. Differences can also be graphically overlaid on the process models.

Resolving Ambiguities in Natural Language Software Requirements

Requirements Engineering is one of the most vital activities in the entire Software Development Life Cycle. The success of the software is largely dependent on how well the users' requirements have been understood and converted into appropriate functionalities in the software. Typically, the users convey their requirements in natural language statements that initially appear easy to state. However, being stated in natural language, the statement of requirements often tends to suffer from misinterpretations and imprecise inferences. As a result, the requirements specified thus, may lead to ambiguities in the software specifications. One can indeed find numerous approaches that deal with ensuring precise requirement specifications. Naturally, an obvious approach to deal with ambiguities in natural language software specifications is to eliminate ambiguities altogether i.e. to use formal specifications. However, the formal methods have been observed to be cost-effective largely for the development of mission-critical software. Due to the technical sophistication required, these are yet to be accepted in the mainstream. Hence, the other alternative is to let the ambiguities exist in the natural language requirements but deal with the same using proven techniques viz. using approaches based on machine learning, knowledge and ontology to resolve them. One can indeed find numerous automated and semi-automated tools to resolve specific types of natural language software requirement ambiguities. However, to the best of our knowledge there is no published literature that attempts to compare and contrast the prevalent approaches to deal with ambiguities in natural language software requirements. Hence, in this paper, we attempt to survey and analyze the prevalent approaches that attempt to resolve ambiguities in natural language software requirements. We focus on presenting a state-of-the-art survey of the currently available tools for ambiguity resolution. The objective of this paper is to disseminate, dissect and analyze the research work published in the area, identify metrics for a comparative evaluation and eventually do the same. At the end, we identify open research issues with an aim to spark new interests and developments in this field.

Ontology-Based Interpretation of Natural Language Philipp Cimiano, Christina Unger, and John McCrae (University of Arminia Bielefeld, Germany) Morgan & Claypool, Synthesis Lectures on Human Language Technologies, March 2014, 178 pages, (doi:10.2200/S00561ED1V01Y201401HLT024) , $45.00

<b>Ontology-Based Interpretation of Natural Language</b> <b>Philipp Cimiano, Christina Unger, and John McCrae</b> (University of Arminia Bielefeld, Germany) Morgan &amp; Claypool, Synthesis Lectures on Human Language Technologies, March 2014, 178 pages, (doi:10.2200/S00561ED1V01Y201401HLT024) , $45.00

FUZZY QUERIES IN BLACK-SCHOLES MODEL FOR FINANCIAL OPTIONS

An approach how to use fuzzy queries in field of financial options is described. It provides the key aspect of information for investor expressed in natural language or queries in natural language. Presented paper indicates the first step in knowledge base creation for investor showing how to apply the corresponding mathematical apparatus to cope with natural language statements in Black-Scholes Model for option pricing.

Using crowd-sourcing to Verify a Radiation Oncology Ontology: a Summer Project

We have been unable to nd a verifi ed, published Radiation Oncology Ontology. We undertook the process of verifying a Radiation Oncology Ontology with a mixture of crowd-sourcing and expert-based approaches to verify relationships in the ontology. We used a natural language based approach to portray concepts and relationships, surveying users to assess the relationships between concepts in the Radiation Oncology ontology. The work used a description of a patient's history expressed in XML. The natural language statements relating concepts are available on a website for veri cation, and readers are invited to complete the survey at http://coi-hs-survey.appspot.com/ to contribute.

Face sketch recognition using sketching with words

The face sketch of the criminal may be one of the crucial evidence in catching the criminal. Face sketch is drawn by the sketch expert on the basis of onlooker’s statement, which is about different human face parts like forehead, eyes, nose, and chin etc. These statements are full of uncertainties e.g. ‘His eyes were not fairly small’. Since the precise interpretation of these natural language statements is a very difficult task. So we need a system that can convert imprecise face description, into a complete face. Therefore we have applied the sketching with words (SWW) technique to design a system that can simulate a face sketch expert. SWW is a methodology in which the objects of computation are fuzzy geometric objects e.g. fuzzy line, fuzzy circle, fuzzy triangle, and fuzzy parallel. These fuzzy objects (f-objects) are formalized by fuzzy geometry (f-geometry) of Zadeh. SWW is inspired by computing with words and fuzzy geometry. Since the onlooker has to granulate face into granule label. Hence the concept of fuzzy granule has applied for face recognition. Different types of face have generated after applying ‘fairly’ and ‘very’ linguistic hedges on face components.

Micropublications: a semantic model for claims, evidence, arguments and annotations in biomedical communications.

BackgroundScientific publications are documentary representations of defeasible arguments, supported by data and repeatable methods. They are the essential mediating artifacts in the ecosystem of scientific communications. The institutional “goal” of science is publishing results. The linear document publication format, dating from 1665, has survived transition to the Web.Intractable publication volumes; the difficulty of verifying evidence; and observed problems in evidence and citation chains suggest a need for a web-friendly and machine-tractable model of scientific publications. This model should support: digital summarization, evidence examination, challenge, verification and remix, and incremental adoption. Such a model must be capable of expressing a broad spectrum of representational complexity, ranging from minimal to maximal forms.ResultsThe micropublications semantic model of scientific argument and evidence provides these features. Micropublications support natural language statements; data; methods and materials specifications; discussion and commentary; challenge and disagreement; as well as allowing many kinds of statement formalization.The minimal form of a micropublication is a statement with its attribution. The maximal form is a statement with its complete supporting argument, consisting of all relevant evidence, interpretations, discussion and challenges brought forward in support of or opposition to it. Micropublications may be formalized and serialized in multiple ways, including in RDF. They may be added to publications as stand-off metadata.An OWL 2 vocabulary for micropublications is available at http://purl.org/mp. A discussion of this vocabulary along with RDF examples from the case studies, appears as OWL Vocabulary and RDF Examples in Additional file 1.ConclusionMicropublications, because they model evidence and allow qualified, nuanced assertions, can play essential roles in the scientific communications ecosystem in places where simpler, formalized and purely statement-based models, such as the nanopublications model, will not be sufficient. At the same time they will add significant value to, and are intentionally compatible with, statement-based formalizations.We suggest that micropublications, generated by useful software tools supporting such activities as writing, editing, reviewing, and discussion, will be of great value in improving the quality and tractability of biomedical communications.

Jointly Learning to Parse and Perceive: Connecting Natural Language to the Physical World

This paper introduces Logical Semantics with Perception (LSP), a model for grounded language acquisition that learns to map natural language statements to their referents in a physical environment. For example, given an image, LSP can map the statement “blue mug on the table” to the set of image segments showing blue mugs on tables. LSP learns physical representations for both categorical (“blue,” “mug”) and relational (“on”) language, and also learns to compose these representations to produce the referents of entire statements. We further introduce a weakly supervised training procedure that estimates LSP’s parameters using annotated referents for entire statements, without annotated referents for individual words or the parse structure of the statement. We perform experiments on two applications: scene understanding and geographical question answering. We find that LSP outperforms existing, less expressive models that cannot represent relational language. We further find that weakly supervised training is competitive with fully supervised training while requiring significantly less annotation effort.

Natural Language Statement to SQL Query Translator

is an organized collection of data. It is created to store large amount of data and retrieve it efficiently in less amount of time. To retrieve data from the database Structured Query Language (SQL) is used. SQL has its own syntax of query. To retrieve correct data from the database this query should be written in proper or correct syntax. Thus users should have sufficient knowledge of SQL to retrieve data. In this paper a light weight technique of converting a natural language statement into equivalent SQL statement is highlighted which when executed on database provides us with the accurate results. The main advantage of this technique is the users which are unknown to the syntax of SQL can also use the system and retrieve data.

On forming joint variables in computing with words

We discuss Zadeh’s idea of computing with words and emphasize its perspective that information provides a restriction on the values variables can assume. We describe the role that the constraint-based semantics plays in translating natural language statements into formal mathematical objects. One task that arises in using this approach is the formulation of joint restrictions on multiple variables from individual information about each of the variables. Our interest here is to extend the capability of the framework of computing with words in the task of forming joint variables with the introduction of the idea of perceived relatedness between variables, a concept closely related to the idea of correlation. We are particularly interested in role that knowledge about perceived relatedness between variables can play in further restricting the possible values of joint then that simple provided by the individual constraints. We look at the problem of joining various types of uncertain variables, possibilistic, probabilistic and Dempster-Shafer belief structures.

Fuzzy quantification: a state of the art

Quantified sentences are a very powerful notion for modelling statements in Natural Language (NL), but in practice they have been used to solve several problems. This paper is intended to offer a global view of the development on this branch until now, focusing in the different approaches dealing with quantification, specially those involving imprecision, called fuzzy quantification. We put attention to the different mechanisms for defining them, the evaluation methods for measuring their fulfilment, as well as the properties they should satisfy.

A Tutorial on Bernoulli Filters: Theory, Implementation and Applications

Bernoulli filters are a class of exact Bayesian filters for non-linear/non-Gaussian recursive estimation of dynamic systems, recently emerged from the random set theoretical framework. The common feature of Bernoulli filters is that they are designed for stochastic dynamic systems which randomly switch on and off. The applications are primarily in target tracking, where the switching process models target appearance or disappearance from the surveillance volume. The concept, however, is applicable to a range of dynamic phenomena, such as epidemics, pollution, social trends, etc. Bernoulli filters in general have no analytic solution and are implemented as particle filters or Gaussian sum filters. This tutorial paper reviews the theory of Bernoulli filters as well as their implementation for different measurement models. The theory is backed up by applications in sensor networks, bearings-only tracking, passive radar/sonar surveillance, visual tracking, monitoring/prediction of an epidemic and tracking using natural language statements. More advanced topics of smoothing, multi-target detection/tracking, parameter estimation and sensor control are briefly reviewed with pointers for further reading.

Fusion of Spatially Referring Natural Language Statements with Random Set Theoretic Likelihoods

Localisation via the fusion of spatially referring natural language statements is considered here. The contribution lies in the underlying problem formulation and a robust modelling framework. Random-set-based estimation is the underlying mathematical formalism. Each statement generates a generalised likelihood function. A Bayesian filter is outlined that takes a sequence of likelihoods generated by multiple statements. The idea is to recursively build a map over the state space that can be used to infer the state.

An Insight Into The Z-number Approach To CWW

The Z-number is a new fuzzy-theoretic concept, proposed by Zadeh in 2011. It extends the basic philosophy of Computing With Words CWW to include the perception of uncertainty of the information conveyed by a natural language statement. The Z-number thus, serves as a model of linguistic summarization of natural language statements, a technique to merge human-affective perspectives with CWW, and consequently can be envisaged to play a radical role in the domain of CWW-based system design and Natural Language Processing NLP. This article presents a comprehensive investigation of the Z-number approach to CWW. We present here: a an outline of our understanding of the generic architecture, algorithm and challenges underlying CWW in general; b a detailed study of the Z-number methodology-where we propose an algorithm for CWW using Z-numbers, define a Z-number based operator for the evaluation of the level of requirement satisfaction, and describe simulation experiments of CWW utilizing Z-numbers; and c analyse the strengths and the challenges of the Z-numbers, and suggest possible solution strategies. We believe that this article would inspire research on the need for inclusion of human-behavioural aspects into CWW, as well as the integration of CWW and NLP.

What should developers be aware of? An empirical study on the directives of API documentation

Application Programming Interfaces (API) are exposed to developers in order to reuse software libraries. API directives are natural-language statements in API documentation that make developers aware of constraints and guidelines related to the usage of an API. This paper presents the design and the results of an empirical study on the directives of API documentation of object-oriented libraries. Its main contribution is to propose and extensively discuss a taxonomy of 23 kinds of API directives.

A computational framework for authoring and searching product design specifications

The development of product design specifications (PDS) is an important part of the product development process. Incompleteness, ambiguity, or inconsistency in the PDS can lead to problems during the design process and may require unnecessary design iterations. This generally results in increased design time and cost. Currently, in many organizations, PDS are written using word processors. Since documents written by different authors can be inconsistent in style and word choice, it is difficult to automatically search for specific requirements. Moreover, this approach does not allow the possibility of automated design verification and validation against the design requirements and specifications. In this paper, we present a computational framework and a software tool based on this framework for writing, annotating, and searching computer-interpretable PDS. Our approach allows authors to write requirement statements in natural language to be consistent with the existing authoring practice. However, using mathematical expressions, keywords from predefined taxonomies, and other metadata the author of PDS can then annotate different parts of the requirement statements. This approach provides unambiguous meaning to the information contained in PDS, and helps to eliminate mistakes later in the process when designers must interpret requirements. Our approach also enables users to construct a new PDS document from the results of the search for requirements of similar devices and in similar contexts. This capability speeds up the process of creating PDS and helps authors write more detailed documents by utilizing previous, well written PDS documents. Our approach also enables checking for internal inconsistencies in the requirement statements.

Regular relations for temporal propositions

AbstractRelations computed by finite-state transducers are applied to interpret temporal propositions in terms of strings representing finite contexts or situations. Carnap–Montague intensions mapping indices to extensions are reformulated as relations between strings that can serve as indices and extensions alike. Strings are related according to information content, temporal span and granularity, the bounds on which reflect the partiality of natural language statements. That partiality shapes not only strings-as-extensions (indicating what statements are about) but also strings-as-indices (underlying truth conditions).

Managing ambiguity in programming by finding unambiguous examples

We propose a new way to raise the level of discourse in the programming process: permit ambiguity, but manage it by linking it to unambiguous examples. This allows programming environments to work with informal descriptions that lack precise semantics, such as natural language descriptions or conceptual diagrams, without requiring programmers to formulate their ideas in a formal language first. As an example of this idea, we present Zones, a code search and reuse interface that connects code with ambiguous natural language statements about its purpose. The backend, called ProcedureSpace, relates purpose statements, static code analysis features, and natural language background knowledge. ProcedureSpace can search for code given statements of purpose or vice versa, and can find code that was never annotated or commented. Since completed Zones searches become annotations, system coverage grows with user interaction. Users in a preliminary study found that reasoning jointly over natural language and programming language helped them reuse code.

An accessible verification environment for UML models of services

Service-Oriented Architectures (SOAs) provide methods and technologies for modelling, programming and deploying software applications that can run over globally available network infrastructures. Current software engineering technologies for SOAs, however, remain at the descriptive level and lack rigorous foundations enabling formal analysis of service-oriented models and software. To support automated verification of service properties by relying on mathematically founded techniques, we have developed a software tool that we called Venus (Verification ENvironment for UML models of Services). Our tool takes as an input service models specified by UML 2.0 activity diagrams according to the UML4 SOA profile, while its theoretical bases are the process calculus COWS and the temporal logic SocL. A key feature of Venus is that it provides access to verification functionalities also to those users not familiar with formal methods. Indeed, the tool works by first automatically translating UML4 SOA models and natural language statements of service properties into, respectively, COWS terms and SocL formulae, and then by automatically model checking the formulae over the COWS terms. In this paper we present the tool, its architecture and its enabling technologies by also illustrating the verification of a classical ‘travel agency’ scenario.

Complex event extraction at PubMed scale

Motivation: There has recently been a notable shift in biomedical information extraction (IE) from relation models toward the more expressive event model, facilitated by the maturation of basic tools for biomedical text analysis and the availability of manually annotated resources. The event model allows detailed representation of complex natural language statements and can support a number of advanced text mining applications ranging from semantic search to pathway extraction. A recent collaborative evaluation demonstrated the potential of event extraction systems, yet there have so far been no studies of the generalization ability of the systems nor the feasibility of large-scale extraction.Results: This study considers event-based IE at PubMed scale. We introduce a system combining publicly available, state-of-the-art methods for domain parsing, named entity recognition and event extraction, and test the system on a representative 1% sample of all PubMed citations. We present the first evaluation of the generalization performance of event extraction systems to this scale and show that despite its computational complexity, event extraction from the entire PubMed is feasible. We further illustrate the value of the extraction approach through a number of analyses of the extracted information.Availability: The event detection system and extracted data are open source licensed and available at http://bionlp.utu.fi/.Contact: jari.bjorne@utu.fi