Joint Prediction of Topics in a URL Hierarchy

Groβhans, Michael; Sawade, Christoph; Scheffer, Tobias; Landwehr, Niels

doi:10.1007/978-3-662-44848-9_33

Cited by 4 publications

(7 citation statements)

References 11 publications

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“…We build upon the work of Ruskey (1981) and Yan and Yeh (2006) , who solved the sub-structure enumeration problems in trees, by providing a non-trivial extension to DAGs. However, we also believe that our algorithm has practical utility for the studies of ontological annotation spaces that have recently gained popularity in structured-output learning in computational biology and other fields ( Grosshans et al , 2014 ; Joachims et al , 2009 ; Movshovitz-Attias et al , 2015 ; Radivojac et al , 2013 ; Sokolov and Ben-Hur, 2010 ). Another related problem is workflow enumeration that may have implications on code analysis and debugging in distributed computing environments ( Sadiq and Orlowska, 2000 ; Zaharia et al , 2010 ).…”

Section: Discussionmentioning

confidence: 95%

“…This work presents a practical algorithm for enumerating consistent subgraphs of directed acyclic graphs. Although this study largely addresses an intellectual challenge of efficient subgraph enumeration, it might have practical utility for the studies of annotation spaces in the biomedical sciences and beyond; e.g., in text mining [8] and computer vision [15]. As ontologies are easy to grow and hard to manually interrogate, we provide a practical tool that can give insights into the complexity of concept annotation tasks [17,11].…”

Section: Discussionmentioning

confidence: 99%

“…It is important to mention that the annotation of biological macromolecules is one of the most interesting examples of concept annotation, primarily because of its biomedical significance but also because of the sizes and the complexity of the available ontologies. Similar situations, however, arise beyond computational biology, as in the fields of text mining ( Grosshans et al , 2014 ) and computer vision ( Movshovitz-Attias et al , 2015 ).…”

Section: A Motivating Examplementioning

confidence: 98%

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Enumerating consistent sub-graphs of directed acyclic graphs: an insight into biomedical ontologies

2018

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MotivationModern problems of concept annotation associate an object of interest (gene, individual, text document) with a set of interrelated textual descriptors (functions, diseases, topics), often organized in concept hierarchies or ontologies. Most ontology can be seen as directed acyclic graphs (DAGs), where nodes represent concepts and edges represent relational ties between these concepts. Given an ontology graph, each object can only be annotated by a consistent sub-graph; that is, a sub-graph such that if an object is annotated by a particular concept, it must also be annotated by all other concepts that generalize it. Ontologies therefore provide a compact representation of a large space of possible consistent sub-graphs; however, until now we have not been aware of a practical algorithm that can enumerate such annotation spaces for a given ontology.ResultsWe propose an algorithm for enumerating consistent sub-graphs of DAGs. The algorithm recursively partitions the graph into strictly smaller graphs until the resulting graph becomes a rooted tree (forest), for which a linear-time solution is computed. It then combines the tallies from graphs created in the recursion to obtain the final count. We prove the correctness of this algorithm, propose several practical accelerations, evaluate it on random graphs and then apply it to characterize four major biomedical ontologies. We believe this work provides valuable insights into the complexity of concept annotation spaces and its potential influence on the predictability of ontological annotation.Availability and implementation https://github.com/shawn-peng/counting-consistent-sub-DAG Supplementary information Supplementary data are available at Bioinformatics online.

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Section: Discussionmentioning

confidence: 95%

Section: Discussionmentioning

confidence: 99%

Section: A Motivating Examplementioning

confidence: 98%

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Enumerating consistent sub-graphs of directed acyclic graphs: an insight into biomedical ontologies

2018

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“…Modern classification approaches increasingly rely on ontological output spaces [20,32]. An ontology O = (V, E) is a directed acyclic graph with a set of vertices (concepts) V and a set of edges (relational ties) E ⊂ V × V .…”

Section: Application To Ontologiesmentioning

confidence: 99%

A new class of metrics for learning on real-valued and structured data

Yang

Jiang

Mathews

et al. 2019

Data Min Knowl Disc

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We propose a new class of metrics on sets, vectors, and functions that can be used in various stages of data mining, including exploratory data analysis, learning, and result interpretation. These new distance functions unify and generalize some of the popular metrics, such as the Jaccard and bag distances on sets, Manhattan distance on vector spaces, and Marczewski-Steinhaus distance on integrable functions. We prove that the new metrics are complete and show useful relationships with f -divergences for probability distributions. To further extend our approach to structured objects such as concept hierarchies and ontologies, we introduce information-theoretic metrics on directed acyclic graphs drawn according to a fixed probability distribution. We conduct empirical investigation to demonstrate intuitive interpretation of the new metrics and their effectiveness on real-valued, highdimensional, and structured data. Extensive comparative evaluation demonstrates that the new metrics outperformed multiple similarity and dissimilarity functions traditionally used in data mining, including the Minkowski family, the fractional L p family, two f -divergences, cosine distance, and two correlation coefficients. Finally, we argue that the new class of metrics is particularly appropriate for rapid processing of high-dimensional and structured data in distance-based learning.

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“…Considering uncertainties in reality, there are various incomplete-information games, and among them, Bayesian games are one of the most important and have a wide range of applications [1, 3,5,12]. In Bayesian games, players cannot obtain complete characteristics of the other players, which are called types subjected to a joint distribution.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Nash equilibrium seeking for multi-agent incomplete-information aggregative games

Zhang,

Qin,

Chen

2023

Kybernetika

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In this paper, we consider a distributed Bayesian Nash equilibrium (BNE) seeking problem in incomplete-information aggregative games, which is a generalization of either Bayesian games or deterministic aggregative games. We handle the aggregation function to adapt to incompleteinformation situations. Since the feasible strategies are infinite-dimensional functions and lie in a non-compact set, the continuity of types brings barriers to seeking equilibria. To this end, we discretize the continuous types and then prove that the equilibrium of the derived discretized model is an -BNE. On this basis, we propose a distributed algorithm for an -BNE and further prove its convergence.

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Joint Prediction of Topics in a URL Hierarchy

Cited by 4 publications

References 11 publications

Enumerating consistent sub-graphs of directed acyclic graphs: an insight into biomedical ontologies

Enumerating consistent sub-graphs of directed acyclic graphs: an insight into biomedical ontologies

A new class of metrics for learning on real-valued and structured data

Bayesian Nash equilibrium seeking for multi-agent incomplete-information aggregative games

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