1,720,974 research outputs found
Mining for Long-Term Dependencies in Causal Graphs
No full textProcess discovery is one of the most challenging tasks in process mining. Based on event data, a process discovery approach generates a process model that captures the behavior recorded in the data. The hybrid miner is a two-step process discovery approach that creates a balance between the advantages of formal modeling and the necessity of remaining informal for vague structures. In the first discovery step, an informal causal graph is constructed based on direct succession dependencies between activities. In the second discovery step, the hybrid miner tries to convert the discovered dependencies into formal constraints. For vague structures where formal constraints cannot be justified, dependencies are depicted informally. In this paper, we reduce the representational bias of the hybrid miner by exploiting causal graph metrics to mine for long-term dependencies. Our evaluation shows that the proposed approach leads to the discovery of more precise models
Discovering hybrid process models with bounds on time and complexity
No full textDiscovering process models from event data is a highly relevant, but also a notoriously difficult, problem. Therefore, it is unsurprising that the biggest share of process mining research is devoted to process discovery. While techniques reported in scientific literature tend to produce process models that are formal, i.e., which mathematically describe the possible behaviors, commercial process mining tools return informal models (merely a “picture” not allowing for any form of formal reasoning). Hybrid process models aim at combining the best of both worlds: they capture behavior that is strongly supported by data and that can be used for formal reasoning, as well as behavior that cannot be represented in clear-cut process constructs or that does not have enough evidence in the data. This paper presents an approach for discovering hybrid Petri nets, which, unlike existing techniques, produces models that have both formal and semi-formal constructs so that even if the behavior in the data is noisy and irregular or it does not fit predefined constructs, causal relationships are still captured. Our evaluation demonstrates the advantages of combining such “deliberate vagueness” with formal guarantees. The ideas presented here are fairly general, and can serve as a foundation for other, new hybrid discovery techniques
POWL: Partially Ordered Workflow Language
No full text92108Process models are used to represent processes in order to support communication and allow for the simulation and analysis of the processes. Many real-life processes naturally define partial orders over the activities they are composed of. Partial orders can be used as a graph-like representation of process behavior. On the one hand, partially ordered graph representations allow us to easily model concurrent and sequential behavior between activities while ensuring simplicity and scalability. On the other hand, partial orders lack the support for typical process constructs such as choice and loop structures. Therefore, in this paper, we present a novel process modeling notation, i.e., the Partially Ordered Workflow Language (POWL). A POWL model is a partially ordered graph extended with control-flow operators for modeling choice and loop structures. A POWL model has a hierarchical structure; i.e., POWL models can be combined into a new model either using a control-flow operator or as a partial order. We propose an initial approach to demonstrate the feasibility of using POWL models for process discovery, and we evaluate our approach based on real-life data
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
POWL: Partially Ordered Workflow Language
No full text84278432Processes in real-life scenarios tend to inherently establish partial orders over their constituent activities. This makes partially ordered graphs viable for process modeling. While partial orders capture both concurrent and sequential interactions among activities in a compact way, they fall short in modeling choice and cyclic behavior. To address this gap, we introduce the Partially Ordered Workflow Language (POWL), a novel language for process modeling that combines traditional hierarchical modeling languages with partial orders. In a POWL model, sub-models are combined into larger ones either as partial orders or using control-flow operators that enable the representation of choice and loop structures. This integration of hierarchical structure and partial orders not only offers an effective solution for process modeling but also provides quality guarantees that make POWL particularly suitable for the automated discovery of process models
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