منابع مشابه
Patent Document Retrieval and Classification at KAIST
In this paper, we propose a method to retrieve similar patent documents for a given patent and classify a given patent. We focus on the one of patents’ characteristics: “patents are structuralized by claims, purposes, effects, embodiments of the invention and so on.” In order to retrieve similar documents from target document set, some specific components to denote the so-called ‘semantic eleme...
متن کاملM - Infosift : a Graph - Based Approach for Multiclass Document Classification
M-INFOSIFT: A GRAPH-BASED APPROACH FOR MULTICLASS DOCUMENT CLASSIFICATION
متن کاملMulticlass Classification Calibration Functions
In this paper we refine the process of computing calibration functions for a number of multiclass classification surrogate losses. Calibration functions are a powerful tool for easily converting bounds for the surrogate risk (which can be computed through well-known methods) into bounds for the true risk, the probability of making a mistake. They are particularly suitable in non-parametric sett...
متن کاملHierarchical Multiclass Object Classification
Humans can use similarity between objects in order to recognize rare objects. They also make many abstract concepts when they see some objects very often. Interestingly, a large part of brain is associated with common classes like faces rather than rare objects like Ostrich. In our work we want to propose a model that has four mentioned characteristics. 1. Use more resources for categories that...
متن کاملInhibition in Multiclass Classification
The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect...
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: Artificial Intelligence Research
سال: 2017
ISSN: 1927-6982,1927-6974
DOI: 10.5430/air.v7n1p1