Can FCA-based Recommender System Suggest a Proper Classifier?

نویسندگان

  • Yury Kashnitsky
  • Dmitry I. Ignatov
چکیده

The paper briefly introduces multiple classifier systems and describes a new algorithm, which improves classification accuracy by means of recommendation of a proper algorithm to an object classification. This recommendation is done assuming that a classifier is likely to predict the label of the object correctly if it has correctly classified its neighbors. The process of assigning a classifier to each object is based on Formal Concept Analysis. We explain the idea of the algorithm with a toy example and describe our first experiments with real-world datasets.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

سیستم پیشنهاد دهنده زمینه‌آگاه برای انتخاب گوشی تلفن همراه با ترکیب روش‌های تصمیم‌گیری جبرانی و غیرجبرانی

Recommender systems suggest proper items to customers based on their preferences and needs. Needed time to search is reduced and the quality of customer’s choice is increased using recommender systems. The context information like time, location and user behaviors can enhance the quality of recommendations and customer satisfication in such systems. In this paper a context aware recommender sys...

متن کامل

Can FCA-based Recommender System Suggest a Proper Classi er?

The paper brie y introduces multiple classi er systems and describes a new algorithm, which improves classi cation accuracy by means of recommendation of a proper algorithm to an object classi cation. This recommendation is done assuming that a classi er is likely to predict the label of the object correctly if it has correctly classi ed its neighbors. The process of assigning a classi er to ea...

متن کامل

Evolutionary User Clustering Based on Time-Aware Interest Changes in the Recommender System

The plenty of data on the Internet has created problems for users and has caused confusion in finding the proper information. Also, users' tastes and preferences change over time. Recommender systems can help users find useful information. Due to changing interests, systems must be able to evolve. In order to solve this problem, users are clustered that determine the most desirable users, it pa...

متن کامل

Use of Semantic Similarity and Web Usage Mining to Alleviate the Drawbacks of User-Based Collaborative Filtering Recommender Systems

  One of the most famous methods for recommendation is user-based Collaborative Filtering (CF). This system compares active user’s items rating with historical rating records of other users to find similar users and recommending items which seems interesting to these similar users and have not been rated by the active user. As a way of computing recommendations, the ultimate goal of the user-ba...

متن کامل

An Effective Algorithm in a Recommender System Based on a Combination of Imperialist Competitive and Firey Algorithms

With the rapid expansion of the information on the Internet, recommender systems play an important role in terms of trade and research. Recommender systems try to guess the user's way of thinking, using the in-formation of user's behavior or similar users and their views, to discover and then propose a product which is the most appropriate and closest product of user's interest. In the past dec...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • CoRR

دوره abs/1504.05473  شماره 

صفحات  -

تاریخ انتشار 2015