Event Process Typing via Hierarchical Optimal Transport
نویسندگان
چکیده
Understanding intention behind event processes in texts is important to many applications. One challenging task this line process typing, which aims tag the with one action label and object describing overall of likely affects respectively. To tackle task, existing methods mainly rely on matching level representation, ignores two characteristics: Process Hierarchy Label Hierarchy. In paper, we propose a Hierarchical Optimal Transport (HOT) method address above problem. Specifically, first explicitly extract hierarchy hierarchy. Then HOT optimally matches types Experimental results show that our model outperforms baseline models, illustrating effectiveness model.
منابع مشابه
Characterization of Lithium Ion Transport Via Dialysis Process
Dialysis is a membrane based separation process in which the concentration gradient across the membrane is the driving force resulting in a flow of material from one side <span style="font-size: 10pt; ...
متن کاملLearning Gaussian Process Kernels via Hierarchical Bayes
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are learned from data using a simple and efficient EM algorithm. This step is nonparametric, in that it does not require a parametric form of covariance function. In a second step, kernel functions are fitted to approximate...
متن کاملHierarchical Conformance Checking of Process Models Based on Event Logs
Process mining techniques aim to extract knowledge from event logs. Conformance checking is one of the hard problems in process mining: it aims to diagnose and quantify the mismatch between observed and modeled behavior. Precise conformance checking implies solving complex optimization problems and is therefore computationally challenging for real-life event logs. In this paper a technique to a...
متن کاملGeodesic Shape Retrieval via Optimal Mass Transport
This paper presents a new method for 2-D and 3-D shape retrieval based on geodesic signatures. These signatures are high dimensional statistical distributions computed by extracting several features from the set of geodesic distance maps to each point. The resulting high dimensional distributions are matched to perform retrieval using a fast approximate Wasserstein metric. This allows to propos...
متن کاملConvex Clustering via Optimal Mass Transport
We consider approximating distributions within the framework of optimal mass transport and specialize to the problem of clustering data sets. Distances between distributions are measured in the Wasserstein metric. The main problem we consider is that of approximating sample distributions by ones with sparse support. This provides a new viewpoint to clustering. We propose different relaxations o...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence
سال: 2023
ISSN: ['2159-5399', '2374-3468']
DOI: https://doi.org/10.1609/aaai.v37i11.26643