MSM: A Method of Multi-Neighborhood Sampling Matching for Entity Alignment
نویسندگان
چکیده
The heterogeneity of knowledge graphs brings great challenges to entity alignment. In particular, the attributes network entities in real world are complex and changeable. key solving this problem is expand neighborhoods different ranges extract neighborhood information efficiently. Based on idea, we propose Multi-neighborhood Sampling Matching Network (MSM), a new KG alignment network, aiming at structural challenge. MSM constructs multi-neighborhood representation learning method learn structure embedding. It then adopts unique sampling cosine cross-matching solve sizes distinct topological structures two entities. To choose right neighbors, apply down-sampling process select most informative towards central target from its one-hop two-hop neighbors. verify effectiveness matching with any corresponding node, give cross-graph conduct detailed research analysis three datasets, which proves MSM.
منابع مشابه
solution of security constrained unit commitment problem by a new multi-objective optimization method
چکیده-پخش بار بهینه به عنوان یکی از ابزار زیر بنایی برای تحلیل سیستم های قدرت پیچیده ،برای مدت طولانی مورد بررسی قرار گرفته است.پخش بار بهینه توابع هدف یک سیستم قدرت از جمله تابع هزینه سوخت ،آلودگی ،تلفات را بهینه می کند،و هم زمان قیود سیستم قدرت را نیز برآورده می کند.در کلی ترین حالتopf یک مساله بهینه سازی غیر خطی ،غیر محدب،مقیاس بزرگ،و ایستا می باشد که می تواند شامل متغیرهای کنترلی پیوسته و گ...
Cross-lingual entity matching and infobox alignment in Wikipedia
Wikipedia has grown to a huge, multi-lingual source of encyclopedic knowledge. Apart from textual content, a large and everincreasing number of articles feature so-called infoboxes, which provide factual information about the articles’ subjects. As the different language versions evolve independently, they provide different information on the same topics. Correspondences between infobox attribu...
متن کاملA neighborhood relevance model for entity linking
Entity Linking is the task of mapping mentions in documents to entities in a knowledge base. One of the crucial tasks is to identify the disambiguating context of the mention, and joint assignment models leverage the relationships within the knowledge base. We demonstrate how joint assignment models can be approximated with information retrieval. We build on pseudo-relevance feedback and use th...
متن کاملA Multi-class Kernel Alignment Method for Image Collection Summarization
This paper proposes a method for involving domain knowledge in the construction of summaries of large collections of images. This is accomplished by using a multi-class kernel alignment strategy in order to learn a kernel function that incorporates domain knowledge (class labels). The kernel function is the basis of a clustering algorithm that generates a subset, the summary, of the image colle...
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: Intelligent Automation and Soft Computing
سال: 2022
ISSN: ['2326-005X', '1079-8587']
DOI: https://doi.org/10.32604/iasc.2022.020218