Manuel Lama

Manuel Lama
University of Santiago de Compostela | USC · Centro Singular de Investigación en Tecnoloxías da Información CITIUS

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144
Publications
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Publications

Publications (144)
Chapter
Full-text available
A short introduction to gamification; Identifying the benefits of gamification in VET education; From the identification of an idea toward the gamification; Gamification and E-learning; Gamification aesthetics; Applicability of gamification in real-life and entrepreneurial based situations
Article
Automated process discovery is a process mining operation that takes as input an event log of a business process and generates a diagrammatic representation of the process. In this setting, a common diagrammatic representation generated by commercial tools is the directly-follows graph (DFG). In some real-life scenarios, the DFG of an event log con...
Preprint
Changes, planned or unexpected, are common during the execution of real-life processes. Detecting these changes is a must for optimizing the performance of organizations running such processes. Most of the algorithms present in the state-of-the-art focus on the detection of sudden changes, leaving aside other types of changes. In this paper, we wil...
Article
In this paper, we propose a framework for the automatic generation of natural language descriptions of healthcare processes using quantitative and qualitative data and medical expert knowledge. Inspired by the demand of novel ways of conveying process mining analysis results of healthcare processes [1], our framework is based on the most widely use...
Chapter
In this paper, we deal with one of the challenges in process mining enhancement: prediction of remaining times in a business process, which is a critical task for many organisations. Our approach consists of (i) defining a number of attributes on the business logs that capture structural information from the traces, (ii) extending the well-known an...
Article
This paper presents the design of a GeoSPARQL query processing solution for scientific raster array data, called GeoLD. The solution enables the implementation of SPARQL endpoints on top of OGC standard Web Coverage Processing Services (WCPS). Thus, the semantic querying of scientific raster data is supported without the need of specific raster arr...
Article
Full-text available
In this work, we present a complete system to produce an automatic linguistic reporting about the customer activity patterns inside open malls, a mixed distribution of classical malls joined with the shops on the street. These reports can assist to design marketing campaigns by means of identifying the best places to catch the attention of customer...
Article
Predictive monitoring of business processes is concerned with the prediction of ongoing cases on a business process. Lately, the popularity of deep learning techniques has propitiated an ever-growing set of approaches focused on predictive monitoring based on these techniques. However, the high disparity of process logs and experimental setups used...
Preprint
Predictive monitoring of business processes is a subfield of process mining that aims to predict, among other things, the characteristics of the next event or the sequence of next events. Although multiple approaches based on deep learning have been proposed, mainly recurrent neural networks and convolutional neural networks, none of them really ex...
Article
Real life business processes change over time, in both planned and unexpected ways. The detection of these changes is crucial for organizations to ensure that the expected and the real behavior are as similar as possible. These changes over time are called concept drifts and its detection is a big challenge in process mining since the inherent comp...
Chapter
Full-text available
In this paper we present the Process-To-Text (P2T) framework for the automatic generation of textual descriptive explanations of processes. P2T integrates three AI paradigms: process mining for extracting temporal and structural information from a process, fuzzy linguistic protoforms for modelling uncertain terms, and natural language generation fo...
Chapter
In this work we present a method to estimate the activity patterns made by shoppers in open malls based on localization information and process mining techniques. We present our smart phone application for logging information from sensors and a process mining system to discover what kind of activity pattern is made by the shoppers based in the key...
Conference Paper
The study aims to examine the current situation of gamification application in entrepreneurial education from the perspective of VET educators from four European countries. Thus, the study was conducted to identify the gamification techniques applied in the entrepreneurship courses developed by the VET teachers and what are the most relevant entrep...
Preprint
Full-text available
Predictive monitoring of business processes is concerned with the prediction of ongoing cases on a business process. Lately, the popularity of deep learning techniques has propitiated an ever-growing set of approaches focused on predictive monitoring based on these techniques. However, the high disparity of process logs and experimental setups used...
Article
Full-text available
Process mining represents a collection of data driven techniques that support the analysis, understanding and improvement of business processes. A core branch of process mining is conformance checking, i.e., assessing to what extent a business process model conforms to observed business process execution data. Alignments are the de facto standard i...
Article
Full-text available
Process mining has become very popular in the last years as a way to analyze the behavior of an organization by offering techniques to discover, monitor and enhance real processes. A key point in process mining is to discover understandable process models. To achieve this goal in complex processes, several simplification techniques have been propos...
Article
Entity Linking (EL) consists of determinating the entities that best represent the mentions in a document. Mentions can be very ambiguous and can refer to different entities in different contexts. In this paper, we present ABACO, a semantic annotation system for Entity Linking (EL) which addresses name ambiguity assuming that the entity that annota...
Conference Paper
Full-text available
Several simplification techniques have been proposed in process mining to improve the interpretability of complex processes, such as the structural simplification of the model or the simplification of the log. However, obtaining a comprehensible model explaining the behaviour of unstructured large processes is still an open challenge. In this paper...
Article
Full-text available
In this paper, we deal with one of the current challenges in process mining enhancement: the prediction of remaining times in business processes. Accurate predictions of the remaining time, defined as the required time for an instance process to finish, are critical in many systems for organisations being able to establish a priori requirements, fo...
Conference Paper
Full-text available
En este artículo se presenta una aproximación basada en técnicas de conformidad de procesos para la resolución de consultas orientadas a definición de modelos de proceso y de condiciones temporales sobre actividades y sobre indicadores clave de negocio.
Preprint
Full-text available
Real life business processes change over time, in both planned and unexpected ways. The detection of these changes is crucial for organizations to ensure that the expected and the real behavior are as similar as possible. These changes over time are called concept drift and its detection is a big challenge in process mining since the inherent compl...
Conference Paper
Full-text available
In this paper, we deal with one of the challenges in process mining enhancement: prediction of remaining times in a business process, which is a critical task for many organisations. Our approach consists of i) defining a number of attributes on the business logs that capture structural information from the traces, ii) extending the well-known anno...
Article
Full-text available
Process mining has emerged as a way to analyze the behavior of an organization by extracting knowledge from event logs and by offering techniques to discover, monitor and enhance real processes. In the discovery of process models, retrieving a complex one, i.e., a hardly readable process model, can hinder the extraction of information. Even in well...
Article
Full-text available
Learning analytics (LA) looks for a better understanding of learning and ways to optimize both the learning and the environments in which it occurs. One of its key research areas is focused on data interoperability, specifically on how to collect and store learning data. Proprietary systems usually store data in their own unique format and thus mak...
Conference Paper
Full-text available
Process mining has focused, among others, on the discovery of frequent behavior with the aim to understand what is mainly happening in a process. Little work has been done involving uncommon behavior, and mostly centered on the detection of anomalies or deviations. But infrequent behavior can be also important for the management of a process, as it...
Article
Including duplicate tasks in the mining process is a challenge that hinders the process discovery, as it is also necessary to find out which events of the log belong to which transitions. To face this problem, we propose SLAD (Splitting Labels After Discovery), an algorithm that uses the local information of the log to enhance an already mined mode...
Conference Paper
Full-text available
Process Mining is concerned with the analysis, understanding and improvement of business processes. One of the most important branches of process mining is conformance checking, i.e. assessing to what extent a business process model conforms to observed business process execution data. Alignments are the de facto standard instrument to compute conf...
Article
In this paper a novel approach to reuse units of learning (UoLs) —such as courses, seminars, workshops, and so on— is presented. Virtual learning environments (VLEs) do not usually provide the tools to export in a standardized format the designed UoLs, making thus more challenging their reuse in a different platform. Taking into account that many o...
Conference Paper
Resumo This article presents SmartLAK an architecture for large data analysis generated by the students during a course through Smart Services. Developed from Big Data technologies, ontologies and architectural patterns, which were combined to facilitate the development of a flexible and interoperable architecture and as a way to support intellige...
Conference Paper
In this paper, we present a big data software architecture that uses an ontology, based on the Experience API specification, to semantically represent the data streams generated by the learners when they undertake the learning activities of a course, e.g., in a course. These data are stored in a RDF database to provide a high performance access so...
Article
Full-text available
In this paper we present a hybrid approach for automatic composition of Web services that generates semantic input-output based compositions with optimal end-to-end QoS, minimizing the number of services of the resulting composition. The proposed approach has four main steps: 1) generation of the composition graph for a request; 2) computation of t...
Conference Paper
Full-text available
In this paper we present a service which automatically generates textual short-term reports for the students' behavior in virtual learning environments. Through this approach, we show how textual reporting is a coherent way of providing information that can complement ---and even enhance--- visual statistics and help teachers to understand in a com...
Article
Edu-AREA is a Web 2.0 application whose main goal is to contribute to teaching innovation. It provides descriptions of educational resources and guidelines that can be used by teachers to create their lesson plans and later to document their teaching experiences. At the current stage of the Edu-AREA development, a main issue is related to the manag...
Article
Full-text available
Prediction of students' performance is one of the most explored issues in educational data mining. To predict if students will achieve the outcomes of the subject based on the previous results enables teachers to adapt the learning design of the subject to the teaching-learning process. However, this adaptation is even more relevant if we could pre...
Article
Process discovery techniques automatically extract the real workflow of a process by analyzing the events that are collected and stored in log files. Although in the last years several process discovery algorithms have been presented, none of them guarantees to find complete, precise and simple models for all the given logs. In this paper we addres...
Article
Full-text available
In this paper we present a theoretical analysis of graph-based service composition in terms of its dependency with service discovery. Driven by this analysis we define a composition framework by means of integration with fine-grained I/O service discovery that enables the generation of a graph-based composition which contains the set of services th...
Article
Including duplicate tasks in the mining process is a challenge that hinders the process discovery as algorithms need an extra effort to find out which events of the log belong to which transitions. To face this problem, we propose an approach that uses the local information of the log to enhance an already mined model by performing a local search o...
Article
The Universia repository is composed of more than 15 million of educational resources. The lack of metadata describing these resources complicates their classification, search and recovery. To overcome this drawback, it was decided to semantically annotate the available educational resources using the ADEGA algorithm. For this objective, we selecte...
Conference Paper
Full-text available
In self-regulated learning, evaluation is a complex task of the teaching process, but even more if students have social media that allow them to build their personal learning environment in different ways. In these kind of virtual environments a large amount of data that needs to be assessed by teachers is generated, and therefore they require tool...
Conference Paper
In this paper a novel approach to facilitate the reuse of units of learning (UoLs) is presented. Typically, e-learning platforms do not provide the means to retrieve designed UoLs in a standardized format to be reused in a different platform, but they have in common that the students and teachers interaction with the system is logged to files. Taki...
Conference Paper
Several process discovery algorithms have been presented in the last years. These approaches look for complete, precise and simple models. Nevertheless, none of the current proposals obtains a good integration between the three objectives and, therefore, the mined models have differences with the real models. In this paper we present a genetic algo...
Conference Paper
One of the most challenging issues in learning analytics is the development of techniques and tools that facilitate the evaluation of the learning activities carried out by learners. In this paper, we faced this issue through a process mining-based platform, called Soft Learn, that is able to discover complete, precise and simple learning paths fro...
Conference Paper
Full-text available
In this paper we present Hipster: a free, open source Java library for heuristic search algorithms. The motivation of developing Hipster is the lack of standard Java search libraries with an extensible, flexible, simple to use model. Moreover, most of the libraries for search algorithms rely on recursive implementations which do not offer fine-grai...
Conference Paper
Edu-AREA is a Web 2.0 application whose main goal is to contribute to teaching innovation through open educational resources, activities and experiences. AREA provides information in the form of descriptions of educational resources and guidelines of activities that can be used by teachers to create their teaching guides and later to document their...
Article
Full-text available
In this paper, a new approach to semantic annotation with linked data in the field of document enrichment is presented. This application has been developed in the domain of Education and contrary to traditional semantic annotation, which relates each relevant term of the document with an instance of the ontology, in our approach relevant terms are...
Article
Full-text available
This paper presents a learning analytics framework for 3D educational virtual worlds that focus on discovering learning flows and checking its conformance through process mining techniques. The core of this framework is an Opensim-based virtual world platform, known as OPENET4VE, that is compliant with the IMS Learning Design specification and that...
Article
Full-text available
El presente trabajo analiza, de forma exploratoria, la experiencia de innovación docente en la configuración de una red social de aprendizaje en una asignatura del Grado de Pedagogía de la Universidad de Santiago de Compostela. La innovación se justifica en las premisas de la enseñanza centrada en el alumno (aprendizaje autónomo, autorregulado y au...
Article
Full-text available
From a computational point of view, the semantic annotation of large-scale data collections is an extremely expensive task. One possible way of dealing with this drawback is to distribute the execution of the annotation algorithm in several computing environments. In this paper, we show how the problem of semantically annotating a large-scale colle...
Article
Full-text available
In this paper, we present a Petri net-based approach that facilitates making structural changes at runtime to units of learning specified in IMS Learning Design (IMS LD). The proposed change model makes use of the hierarchical Petri net model derived from IMS LD and a page substitution mechanisms to replace learning flow components on the fly. As a...
Article
In this paper, an IMS LD engine based on a Petri net model that represents the operational semantics of units of learning based on this specification is presented. The Petri nets of this engine, which is called OPENET4LD, verify the structural properties that are desirable for a learning flow and also facilitate the adaptation of the engine if pote...
Conference Paper
The aim of this work is to present a dynamic QoS-aware semantic web service composition algorithm that finds the minimal solution graph that satisfies the composition request considering multiple QoS criteria and semantic input-output message structure matching restrictions. Our proposal starts computing an initial solution by selecting only those...
Article
In this paper, we present a Petri net-based approach for modeling the choreography of semantic Web services which are described following the OWL-S specification. In our approach, each control construct of the OWL-S choreography is represented through a Petri net pattern that captures formally its operational semantics. The main difference between...
Conference Paper
In this paper an approach for taking advantage of the information available in the social network tools of Learning Management Systems is presented. Specifically, our objective is to determine domain experts from their participation in the social networks. Our approach first integrates the different sources of information through an ontology based...
Article
The ability of web services to build and integrate loosely-coupled systems has attracted a great deal of attention from researchers in the field of the automatic web service composition. The combination of different web services to build complex systems can be carried out using different control structures to coordinate the execution flow and, ther...
Article
In this paper we present an approach for improving a specific class of semantic annotation, that relates a term of the document with a (sub)tree of the ontology, instead of linking a term with a single concept of the ontology. An important part of this class of annotation is filtering the relevant (sub)nodes and relations, because the returned grap...
Conference Paper
In this paper we propose two novel multicriteria recommendation algorithms and present a comparison with other recommendation approaches in the gastronomic domain. The motivation comes from the fact that traditional single criterion approaches consider that two users share the same taste when they provide similar global ratings on the experienced i...
Conference Paper
Full-text available
Service Oriented Architectures and web service technology are becoming popular in recent years. As more web services can be used over the Internet, the need to find efficient algorithms for web services composition that can deal with large amounts of services becomes important. These algorithms must deal with different issues like performance, sema...
Conference Paper
Learning objects have arisen in response to the need of high-quality and reusable instructional materials. The repositories that hold learning objects allow educators to create and share their instructional contents in an organized infrastructure and where information should be easily searchable. Therefore, a key point of these repositories is the...
Conference Paper
Full-text available
This paper presents a recommendation algorithm that suggests relevant collaborative teams of teachers to the coordinators of courses or units of learning. This work is motivated by the need of automating and facilitating the search of experts that could contribute to the design and development of units of learning in collaborative authoring tools....
Conference Paper
Nowadays a greater number of domains require an improvement in the flexibility of its e-learning systems to so facilitate the adaptation of their course to their user needs. Some adaptive learning systems have been developed in recent years to cover part of these needs, and provide the ability to redirect the student learning flow based on the know...
Conference Paper
A way of describing the teaching, learning interactions and activities is through Educational Modeling Languages. These languages are formalized so an interpreter can automatically coordinate the activities. However, like for example IMS LD, these languages are usually difficult to understand causing that instructors do not always understand the wa...