In this paper, we describe the people attribute extraction system of the CASIANED team for the second Web People search evaluation (WePS-2). We develop an attribute extraction system based on information extraction. Firstly the attribute candidates for every attribute class are extracted using several different information extraction techniques; then these candidates are verified through classi...

By analyzing the current situation of inventory management of enterprises of fresh agricultural products in Handan city as an example and based on the nature of fresh agricultural products, this paper points out the defect and disadvantage of single classification standard of ABC classification method in inventory classification; and applies the improved classification method based on ABC class...

This paper explores the use of the naive Bayes classifier as the basis for personalized spam filters. Various machine learning algorithms, including variants of naive Bayes, have previously been used for this purpose, but the author’s implementation using word position based attribute vectors gives very good results when tested on several publicly available corpora. The effect of various forms ...

In this paper, we present two novel class-based weighting methods for the Euclidean nearest neighbor algorithm and compare them with global weighting methods considering empirical results on a widely accepted time series classification benchmark dataset. Our methods provide higher accuracy than every global weighting in nearly half of the cases and they have better overall performance. We concl...

Due to the low performance caused by the traditional "embedded" watermark and the shortages about low accuracy and weak anti-aggressive of single-attribute birthmark in checking obfuscated software theft, a software identification scheme is proposed which is based on classification of multi-dimensional features. After disassembly analysis and static analysis on protecting software and its resis...

With the exponential growth of information on the WWW, it is becoming increasingly difficult to find and organize relevant documents. Automatic text classification has been considered as a solution to the problem with its focus mostly on the subject or content of text [1]. Recently, researchers have realized that user information needs are not just based on the subject of a document but also on...

In the paper nine different approaches to missing attribute values are presented and compared. Ten input data files were used to investigate the performance of the nine methods to deal with missing attribute values. For testing both naive classification and new classification techniques of LERS (Learning from Examples based on Rough Sets) were used. The quality criterion was the average error r...

User attribute classification aims to identify users’ attributes (e.g., gender, age and profession) by leveraging user generated content. However, conventional approaches to user attribute classification focus on single attribute classification involving only one user attribute, which completely ignores the relationship among various user attributes. In this paper, we confront a novel scenario ...