Stability Analysis of Learning Algorithms for Ontology Similarity Computation
نویسندگان
چکیده
منابع مشابه
Stability and Similarity of Link Analysis Ranking Algorithms
Recently, there has been a surge of research activity in the area of link analysis ranking, where hyperlink structures are used to determine the relative authority of webpages. One of the seminal works in this area is that of Kleinberg [Kleinberg 98], who proposed the HITS algorithm. In this paper, we undertake a theoretical analysis of the properties of the HITS algorithm on a broad class of r...
متن کاملOntology Similarity Measuring and Ontology Mapping Algorithms Via Graph Semi-Supervised Learning
Ontology similarity calculation is important research topics in information retrieval and widely used in biology and chemical. By analyzing the technology of semi-supervised learning, we propose the new algorithm for ontology similarity measure and ontology mapping. The ontology function is obtained by learning the ontology sample data which is consisting of labeled and unlabeled ontology data....
متن کاملAlgorithm of Ontology Similarity Measure Based on Similarity Kernel Learning
Ontology, as a structured conceptual model of knowledge representation and storage, has widely been used in biomedical and pharmaceutical research. The nature of the ontology application is to get the similarity between ontology vertices, and thus reveal the similarity of their corresponding concepts and intrinsic relationships. The similarity for all pairs of vertices forms a similarity matrix...
متن کاملanalysis of ruin probability for insurance companies using markov chain
در این پایان نامه نشان داده ایم که چگونه می توان مدل ریسک بیمه ای اسپیرر اندرسون را به کمک زنجیره های مارکوف تعریف کرد. سپس به کمک روش های آنالیز ماتریسی احتمال برشکستگی ، میزان مازاد در هنگام برشکستگی و میزان کسری بودجه در زمان وقوع برشکستگی را محاسبه کرده ایم. هدف ما در این پایان نامه بسیار محاسباتی و کاربردی تر از روش های است که در گذشته برای محاسبه این احتمال ارائه شده است. در ابتدا ما نشا...
15 صفحه اولStability of learning algorithms
is consistent. In some cases, the UCEM property is both necessary and sufficient for learnability — for example, in the binary classification setting, where Z = (X ,Y ) with arbitrary X , Y ∈ {0,1}, and f (Z ) = f (X ,Y ) taking values in {0,1}. However, it is easy to see that, in general, one can have learnability without the UCEM property. For example, suppose that the function class F is suc...
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: Abstract and Applied Analysis
سال: 2013
ISSN: 1085-3375,1687-0409
DOI: 10.1155/2013/174802