Document retrieval has been an important research problem over many years in the information retrieval community. State-of-the-art techniques utilize various methods in matching documents to a given document including keywords, phrases, and annotations. In this paper, we propose a new approach for document retrieval that utilizes predications (subject-predicate-object triples) extracted from th...

reply to the letter sent by prof. viroj wiwanitkit entitled “radiofrequency radiation and human ferritin”   authors of the article entitled “effects of radiofrequency radiation on human ferritin: an in-vitro enzymun assay” [1] would like to express their satisfactions, since the manuscript have been accessed and used as an element of reflection by a renowned researchers such as prof. wiwanitkit...

In recent years, many private corporations and government organizations have digitized corpuses of legacy paper documents. Often, these organizations hope to take advantage of digital representations to transform costly manual tasks associated with paper archives into less-costly computer-assisted tasks. The most common approach toward automated information extraction is through inverted indexi...

Text summarization system can save the time for user when reading large number of documents. The summary of text summarization system usually composed of meaningful sentence which represent content of text. The relations between keyword usually come from their cooccurrences in document. This study using hierarchical clustering method cluster sentences and apply concept formal analysis to find o...

As shown in Wikipedia, tagging or cross-linking through major keywords in a document collection improves not only the readability of documents but also responsive and adaptive navigation among related documents. In recent years, the Semantic Web has increased the importance of social tagging as a key feature of the Web 2.0 and, as its crucial phenotype, Tag Cloud has emerged to the public. In t...

Keywords are index terms that contain most important information. Automatic keyword extraction is the task to identify a small set of words , keyphrases or keywords from a document that can describe the meaning of document. Keyword extraction is considered as core technology of all automatic processing for text materials. In this paper, a Survey of Keyword Extraction techniques have been presen...

Document summarization is a technique aimed to automatically extract main ideas from electronic documents. In this paper, we propose a novel algorithm, called TriangleSum for key sentence extraction from single document based on graph theory. The algorithm builds a dependency graph for the underlying document based on co-occurrence relation as well as syntactic dependency relations. The nodes r...

In this paper we introduce and analyze two improvements to GDClust [1], a system for document clustering based on the co-occurrence of frequent subgraphs. GDClust (Graph-Based Document Clustering) works with frequent senses derived from the constraints provided by the natural language rather than working with the co-occurrences of frequent keywords commonly used in the vector space model of doc...

The reliable optical character recognition is not available for scripts of Indian languages. Thus, the only way to make legacy documents in Indian languages available on the web is by scanning them. This work is an attempt to cater to the need for a better representation and efficient storage technique for Indian language documents and their near perfect regeneration at the browser. We work wit...