The visualisation of textual concordances has seen little change since the proposal of the keyword-in-context indexing technique in the 1950s. This report details an investigation of the current state of the art in concordance visualisation. The investigation lead to the the expansion of context trees to a new graph based representation of concordance lists. This representation is explained in ...

Most existing XML stream processing systems adopt full structured query languages, such as XPath or XQuery, but they are difficult for ordinary users to learn and use. Keyword search is a user-friendly information discovery technique that has been extensively studied for text documents. This paper presents an XML stream filter system called XKFilter, which is the first system for supporting key...

Geo-textual indices play an important role in spatial keyword querying. The existing geo-textual indices have not been compared systematically under the same experimental framework. This makes it difficult to determine which indexing technique best supports specific functionality. We provide an all-around survey of 12 stateof-the-art geo-textual indices. We propose a benchmark that enables the ...

In this paper, we propose a technique for detecting keywords quickly from a very large speech database without using a large memory space. To accelerate searches and save memory, we used a suffix array as the data structure and applied phoneme-based DP-matching. To avoid an exponential increase in the process time with the length of the keyword, a long keyword is divided into short sub-keywords...

Keyword search is emerging as the standard way to access information of any kind. Following this trend, several approaches to keyword search over relational databases have been proposed recently. Most of them build tree-shaped solutions that connect tuples matching the given keywords. In this paper, we propose a novel technique to this problem that generates solutions by simply combining joinin...

Keywords can be considered as condensed versions of documents and short forms of their summaries. In this paper, the problem of automatic extraction of keywords from documents is treated as a supervised learning task. A lexical chain holds a set of semantically related words of a text and it can be said that a lexical chain represents the semantic content of a portion of the text. Although lexi...

This paper presents a new majority voting technique that combines the two basic modalities of Web images textual and visual features of image in a re-annotation and search based framework. The proposed framework considers each web page as a voter to vote the relatedness of keyword to the web image, the proposed approach is not only pure combination between image low level feature and textual fe...

Abbreviation Completion is a novel technique to improve the efficiency of code-writing by supporting code completion of multiple keywords based on non-predefined abbreviated input—a different approach from conventional code completion that finds one keyword at a time based on an exact character match. Abbreviated input is expanded into keywords by a Hidden Markov Model learned from a corpus of ...

In this paper, we present the results of a project that seeks to transform low-level features to a higher level of meaning. This project concerns a technique, latent semantic indexing (LSI), in conjunction with normalization and term weighting, which have been used for full-text retrieval for many years. In this environment, LSI determines clusters of co-occurring keywords, sometimes, called co...