Supporting collaborative hierarchical classification: Bookmarks as an example
نویسندگان
چکیده
منابع مشابه
Supporting collaborative hierarchical classification: Bookmarks as an example
Bookmarks (or Favorites, Hotlists) are a popular strategy to relocate interesting websites on the WWW by creating a personalized URL repository. Most current browsers offer a facility to locally store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable organization structure. This paper presents a novel collabo...
متن کاملHierarchical Text Classification for Supporting Educational Programs
More than two decades have passed since the first design of the CONSTRUE system [2], a powerful rule-based model for the categorization of Reuters news. Nowadays, statistical approaches are well assessed and they allow for an easy design of text classification (TC) systems. Additionally, the Web has emphasized the need of approaches for digesting large amount of textual information and making i...
متن کاملCollaborative error reduction for hierarchical classification
Hierarchical classification (HC) is a popular and efficient way for detecting the semantic concepts from the images. The conventional method always selects the branch with the highest classification response. This branch selection strategy has a risk of propagating classification errors from higher levels of the hierarchy to the lower levels. We argue that the local strategy is too arbitrary, b...
متن کاملClassification on High Dimensional Metabolic Data: Phenylketonuria as an Example
Tandem mass spectrometry is a promising new screening technology which permits screening within one analytical run not only for phenylketonuria (PKU) but also for a wide range of other metabolic disorders in newborns. We investigated two symbolic supervised machine learning techniques logistic regression analysis (LRA) and decision trees (DT), where the knowledge is represented in an explicit w...
متن کاملHierarchical Transductive Classification from Textual Data with Relevant Example Selection
In many textual repositories, documents are organized in a hierarchy of categories to support a thematic search by browsing topics of interests. In this paper we present a novel approach for automatic classification of documents into a hierarchy of categories that works in the transductive setting and exploits relevant example selection. While the transductive learning setting permits to classi...
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: Computer Networks
سال: 2007
ISSN: 1389-1286
DOI: 10.1016/j.comnet.2007.06.014