Summary form only given.The hierarchical Edge-Guided techniques (called E-Gfc) enhance the original E-G approach to support high-order text statistics. These consider the same graph-based model to represent an extended input alphabet obtained by using a variant of the Re-Pair algorithm. E-Gfc adapts the previous coding scheme to grasp the features of the bit-oriented canonical Huffman code chosen as output alphabet.

The word-codeword mapping technique allows words to be managed in PPM modelling when a natural language text file is being compressed. The main idea for managing words is to assign them codes in order to improve the compression. The previous work was focused on proposing several mapping adaptive algorithms and evaluating them. In this paper, we propose a semi-static word-codeword mapping method that takes advantage of by previous knowledge of some statistical data of the vocabulary. We test our idea implementing a basic prototype, dubbed mppm2, which also retains all the desirable features of a word-codeword mapping technique. The comparison with other techniques and compressors shows that our proposal is a very competitive choice for compressing natural language texts. In fact, empirical results show that our prototype achieves a very good compression for this type of documents.

This paper describes a novel approach for bilingual parallel corpora (bitexts) compression. The approach takes advantage of the fact that the two texts that form a bitext are mutual translations. First, the two texts are aligned both at the sentence and the word level. Then, word alignments are used to define biwords, that is, pairs of two words, each one from a different text, that are mutual translations. Finally, a biword-based PPM compressor is applied. The results obtained compressing the two texts of the bitext together improve the compression ratios achieved when both texts are independently compressed through a word-based PPM compressor; thus, saving storage and transmission costs.

The geographic scope of Web pages is becoming an essential dimension of Web search, especially for mobile users. This paper shows a multistage method for assigning a geographic focus to Web pages (GeoReferencing) according to their text contents. We suggest several heuristics for the disambiguation toponyms and a scoring procedure for focus determination. Furthermore, we provide an experimental methodology for evaluating the accuracy. Finally, we obtained promising results of over 70% accuracy with a city-level resolution.

Abstract The authors describe Lempel‐Ziv to Compress Structure (LZCS), a novel Lempel–Ziv approach suitable for compressing structured documents. LZCS takes advantage of repeated substructures that may appear in the documents, by replacing them with a backward reference to their previous occurrence. The result of the LZCS transformation is still a valid structured document, which is human‐readable and can be transmitted by ASCII channels. Moreover, LZCS transformed documents are easy to search, display, access at random, and navigate. In a second stage, the transformed documents can be further compressed using any semistatic technique, so that it is still possible to do all those operations efficiently; or with any adaptive technique to boost compression. LZCS is especially efficient in the compression of collections of highly structured data, such as extensible markup language (XML) forms, invoices, e‐commerce, and Web‐service exchange documents. The comparison with other structure‐aware and standard compressors shows that LZCS is a competitive choice for these type of documents, whereas the others are not well‐suited to support navigation or random access. When joined to an adaptive compressor, LZCS obtains by far the best compression ratios.

Summary form only given. We explore the use of words as the basic unit in PPM. Our goal has been carried out following two different ways: (1) we have added an additional previous layer to PPM that allows to replace words by two bytes codewords, and then these codewords will be codified with a conventional PPM; and (2) we have modified PPM so that it considers the words like symbols instead of characters, thus this PPM variation will make their predictions on consecutive words sequences handling words. Experimental results show that both techniques improve character-based compressors (including the PPM version used and adapted in the prototypes) for files of size greater than 1 Mb, due to the overload in storing the vocabulary. Prototype 1 accomplished compression in the same time but requiring slightly more memory (closest to PPMDi as the size grows) and it is about 5000% faster and it uses a 92% less of memory than PPMZ. Prototype 2 demanding much more time and memory and it is similar to the PPMZ, one of the better PPM variations

This paper discusses the possibility of considering the text structure in the context of compressed structured documents. This paper also proposes a compression technique for structured documents, called SCMPPM, which combines the prediction by partial matching technique with structural contexts model idea, which takes advantage of the context information usually implicit in the structure of the text. The experimental results shows significant gains over the methods that are insensitive to the structure and over the current methods that consider the structure. This method actually improves compression ratios with respect to the basic SCM technique.

We describe a novel Lempel-Ziv approach suitable for compressing structured documents, called LZCS, which takes advantage of redundant information that can appear in the structure. The main idea is that frequently repeated subtrees may exist and these can be replaced by a backward reference to their first occurrence. The main advantage is that compressed documents generated by LZCS are easy to display, access at random, and navigate. In a second stage, processed documents can be further compressed using some semiadaptive technique, so that random access and navigability remain possible. LZCS is especially efficient to compress collections of highly structured data, such as XML forms, invoices, e-commerce and web-service exchange documents. The comparison against structure-based and standard compressors shows that LZCS is a competitive choice for this type of documents, while the others are not well-suited to support navigation or random access.

No abstract available.

Many document collections contain documents that have significant structure. Structured document retrieval requires different models and interfaces from standard Information Retrieval. An Information Retrieval system dealing with structured documents has to enable a user to query, browse retrieved documents, and provide query refinement and relevance feedback based not only on full documents but also on specific parts of them, according to their structure. Currently, very few IR systems enable such level of flexibility and interaction, because of limitations in indexing and retrieval models and in interfaces. In this paper, we present the design of a new graphical user interface for structured document retrieval. This interface provides the user with an intuitive and yet powerful set of tools for structured document searching, retrieved list navigation, and search refinement. 1

We present a new model to query document databases by content and structure. The main merits of the model are: it allows rich structure in the documents; the query algebra is intuitive (moreover, complemented by a visual query language) and powerful; it is efficiently implementable; it can be built on top of a traditional indexing system or even with no index at all; it is strongly oriented to user-definable relevance ranking instead of boolean logic; and it allows flexible visualization of results in terms of structure, contents and highlighting of user-defined important parts in the query.

It is widely accepted that object-oriented constructions can be used as a pertinent basis for the support of distributed systems consisting of concurrently executing objects that communicate and interoperate among them. In this context, distributed object systems are represented from a process-oriented perspective which uses the process as the basic modelling structure. This point of view allows us to model concurrent objects as a collection of interacting processes, each of them describing a pattern of behaviour. We aim to provide a formal foundation for object-oriented constructions. To do so, we present a formal model of concurrent objects based on a well-defined process theory, the /spl pi/-calculus, which offers a very effective mechanism of specification and verification. The election of the /spl pi/-calculus is justified by some of its features, e.g., mobility and higher-order constructions, for they will be essential to the description of some object behaviour and constructions.