NLP4BPM : Natural language processing tools for business process management

Business Process Management is facing a drift in the way process information is used within an organization. To reach a wide audience, organizations keep parallel representations of process information, thus making the processes to be understandable by everyone. However, this poses a challenge on the synchronization and transformation between different process representations. NLP4BPM is an environment to support such crucial tasks. It combines Natural Language Processing tools with process-oriented techniques, and through its web-based interface can be easily accessed from any device.Peer ReviewedPostprint (author's final draft

Model-Agnostic process modelling

Modeling techniques in Business Process Management often suffer from low adoption due to the variety of profiles found in organizations. This project aims to provide a novel alternative to BPM documentation, ATD, based on annotated process descriptions in natural language

From process models to chatbots

The effect of digital transformation in organizations needs to go beyond automation, so that human capabilities are also augmented. A possibility in this direction is to make formal representations of processes more accessible for the actors involved. On this line, this paper presents a methodology to transform a formal process description into a conversational agent, which can guide a process actor through the required steps in a user-friendly conversation. The presented system relies on dialog systems and natural language processing and generation techniques, to automatically build a chatbot from a process model. A prototype tool – accessible online – has been developed to transform a process model in BPMN into a chatbot, defined in Artificial Intelligence Marking Language (AIML), which has been evaluated over academic and industrial professionals, showing potential into improving the gap between process understanding and execution.Peer ReviewedPostprint (author's final draft

Unleashing textual descriptions of business processes

Textual descriptions of processes are ubiquitous in organizations, so that documentation of the important processes can be accessible to anyone involved. Unfortunately, the value of this rich data source is hampered by the challenge of analyzing unstructured information. In this paper we propose a framework to overcome the current limitations on dealing with textual descriptions of processes. This framework considers extraction and analysis and connects to process mining via simulation. The framework is grounded in the notion of annotated textual descriptions of processes, which represents a middle-ground between formalization and accessibility, and which accounts for different modeling styles, ranging from purely imperative to purely declarative. The contributions of this paper are implemented in several tools, and case studies are highlighted.This work has been supported by MINECO and FEDER funds under grant TIN2017-86727-C2-1-R.Peer ReviewedPostprint (author's final draft

Bridging the gap between textual and formal business process representations

Tesi en modalitat de compendi de publicacionsIn the era of digital transformation, an increasing number of organizations are start ing to think in terms of business processes. Processes are at the very heart of each business, and must be understood and carried out by a wide range of actors, from both technical and non-technical backgrounds alike. When embracing digital transformation practices, there is a need for all involved parties to be aware of the underlying business processes in an organization. However, the representational complexity and biases of the state-of-the-art modeling notations pose a challenge in understandability. On the other hand, plain language representations, accessible by nature and easily understood by everyone, are often frowned upon by technical specialists due to their ambiguity. The aim of this thesis is precisely to bridge this gap: Between the world of the techni cal, formal languages and the world of simpler, accessible natural languages. Structured as an article compendium, in this thesis we present four main contributions to address specific problems in the intersection between the fields of natural language processing and business process management.A l’era de la transformació digital, cada vegada més organitzacions comencen a pensar en termes de processos de negoci. Els processos són el nucli principal de tota empresa i, com a tals, han de ser fàcilment comprensibles per un ampli ventall de rols, tant perfils tècnics com no-tècnics. Quan s’adopta la transformació digital, és necessari que totes les parts involucrades estiguin ben informades sobre els protocols implantats com a part del procés de digitalització. Tot i això, la complexitat i biaixos de representació dels llenguatges de modelització que actualment conformen l’estat de l’art sovint en dificulten la seva com prensió. D’altra banda, les representacions basades en documentació usant llenguatge natural, accessibles per naturalesa i fàcilment comprensibles per tothom, moltes vegades són vistes com un problema pels perfils més tècnics a causa de la presència d’ambigüitats en els textos. L’objectiu d’aquesta tesi és precisament el de superar aquesta distància: La distància entre el món dels llenguatges tècnics i formals amb el dels llenguatges naturals, més accessibles i senzills. Amb una estructura de compendi d’articles, en aquesta tesi presentem quatre grans línies de recerca per adreçar problemes específics en aquesta intersecció entre les tecnologies d’anàlisi de llenguatge natural i la gestió dels processos de negoci.Postprint (published version

Formal Reasoning on Natural Language Descriptions of Processes

The existence of unstructured information that describes processes represents a challenge in organizations, mainly because this data cannot be directly referred into process-aware ecosystems due to ambiguities. Still, this information is important, since it encompasses aspects of a process that are left out when formalizing it on a particular modelling notation. This paper picks up this challenge and faces the problem of ambiguities by acknowledging its existence and mitigating it. Specifically, we propose a framework to partially automate the elicitation of a formal representation of a textual process description, via text annotation techniques on top of natural language processing. The result is the ATDP language, whose syntax and semantics are described in this paper. ATDP allows to explicitly cope with several interpretations of the same textual description of a process model. Moreover, we link the ATDP language to a formal reasoning engine and show several use cases. A prototype tool enabling the complete methodology has been implemented, and several examples using the tool are provided.Peer ReviewedPostprint (author's final draft