Learning based Clustering for the Automatic Annotations from Web Databases
نویسندگان
چکیده
منابع مشابه
Semi-Automatic Semantic Annotations for Web Documents
Semantic annotation of the web documents is the only way to make the Semantic Web vision a reality. Considering the scale and dynamics of worldwide web, the largest knowledge base ever built, it becomes clear that we cannot afford to annotate web documents manually. In this work we propose a generic domain-independent architecture for semi-automatic semantic annotation, basing on the lightweigh...
متن کاملFalse Annotations of Proteins: Automatic Detection via Keyword-Based Clustering
Computational protein annotation methods occasionally introduce errors. False-positive (FP) errors are annotations that are mistakenly associated with a protein. Such false annotations introduce errors that may spread into databases through similarity with other proteins. We present a protein-clustering method that enables automatic separation of FP from true-positive hits. The method is based ...
متن کاملPattern-based automatic taxonomy learning from the Web
The construction of taxonomies is considered as the first step for structuring domain knowledge. Many methodologies have been developed in the past for building taxonomies from classical information repositories such as dictionaries, databases or domain text. However, in the last years, scientists have started to consider the Web as valuable repository of knowledge. In this paper we present a n...
متن کاملThe Prosodizer - Automatic Prosodic Annotations of Speech Synthesis Databases
Prosodic annotations are used for locating and characterizing prominent parts in utterances as well as identifying and describing boundaries of coherent stretches of speech. In speech synthesis prosodic annotations can be used to improve the unit selection process and subsequently yield more natural sounding synthesis. A method for automatic prosodic annotations of speech is described in this p...
متن کاملClustering Deep Web Databases Semantically
Deep Web database clustering is a key operation in organizing Deep Web resources. Cosine similarity in Vector Space Model (VSM) is used as the similarity computation in traditional ways. However it cannot denote the semantic similarity between the contents of two databases. In this paper how to cluster Deep Web databases semantically is discussed. Firstly, a fuzzy semantic measure, which integr...
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: International Journal of Computer Applications
سال: 2015
ISSN: 0975-8887
DOI: 10.5120/19838-1692