Titlebook: Information Retrieval Technology; 6th Asia Information Pu-Jen Cheng,Min-Yen Kan,Preslav Nakov Conference proceedings 2010 Springer Berlin H

tangle

博愛家

Multi-viewpoint Based Similarity Measure and Optimality Criteria for Document Clusteringel concept of similarity measure among objects and its related clustering algorithms. The similarity between two objects within a cluster is measured from the view of all other objects outside that cluster. As a result, two optimality criteria are formulated as the objective functions for the cluste

hankering

A Text Classifier with Domain Adaptation for Sentiment Classifications algorithm is often employed to argument the labeled data with the unlabeled ones. However, such an approach assumes the distributions of these two sets of data are identical, which may not hold in practice and often results in inferior performance..We propose a semi-supervised algorithm, called Ra

linear

真繁榮

合群

Score Estimation, Incomplete Judgments, and Significance Testing in IR Evaluationevance judgments that are associated with them. To keep experimental costs under control, partial relevance judgments are used rather than exhaustive ones, admitting a degree of uncertainty into the per-topic effectiveness scores being compared. Here we explore the design options that must be consid

gnarled

: A Meta-search Engine Based on Multiple Ontologiescally-based semantic relatedness measures. . attempts to employ knowledge represented by multiple ontologies for both query translation and returned results merging. In addition, it utilizes semantic relatedness measures to address the issue of missing background knowledge in the used ontologies. Th

Daily-Value

Co-HITS-Ranking Based Query-Focused Multi-document Summarizationnk and HITS to incorporate diverse relationships into the process of sentence evaluation. Both the homogeneous relationships between sentences and the heterogeneous relationships between sentences and documents have been investigated in the past. However, for query-focused multi-document summarizati

高深莫測

Advanced Training Set Construction for Retrieval in Historic Documentsg this mapping, we have developed a rule-based approach. The bottleneck of this method has been the training set construction for the algorithm where an expert has to assign manually current word forms to historic spelling variants. As a better solution, we apply a spell checker on a corpus of histo

檔案

Ontology-Driven Semantic Digital Librarytic information retrieval for digital library from the perspective of semantic technology and ontology. We proposed an approach for managing, organizing and populating ontology for document collections in digital library. In this sense the document metadata and content are inserted and populated to