Cameleon (programming language)

Abstract: The web is rapidly becoming the universal repository of information. A major challenge is the ability to support the effective flow of information among the sources and services on the web and their interconnection with legacy systems that were designed to operate with traditional relational databases. This paper describes a technology and infrastructure to address these needs, based on the design of a web wrapper engine called Cameleon. Cameleon extracts data from web pages using declarative specification files that define extraction rules. Cameleon is based on the relational model and designed to work as a relational front-end to web sources. ODBC drivers can be used to send SQL queries to Cameleon. Query results by Cameleon are presented in either XML or HTML table formats. Users can also easily call Cameleon from other applications (e.g. Microsoft Excel by using Cameleon web query file (Cameleon.iqy)). Unlike its predecessor, Grenouille, Cameleon lets users segment web pages and define independent extraction patterns for each attribute. The HTTPClient package used in Cameleon supports both GET and POST methods and is able to deal with authentication, redirection, and cookie issues when connecting to web pages.

Abstract: Pattern-based approaches for knowledge identification in texts assume that linguistic regularities always characterise the same kind of knowledge, such as semantic relations. In this paper, we report the experimental evaluation of a large set of patterns using an ontology enrichment tool: Cameleon. Results emphasize the strong influence of the corpus on pattern efficiency and on their meaning. This influence confirms two of the hypotheses that motivated to define Cameleon as a support used in a human-driven process: (1) patterns and relations must be adapted to each project; (2) human interpretation is required to decide how to report the pieces of knowledge identified with patterns in the ontology.

Abstract: Pattern-based approaches for knowledge identification in texts assume that linguistic regularities always characterise the same kind of knowledge, such as semantic relations. We report the experimental evaluation of a large set of patterns using an ontology enrichment tool: Cameleon. Results underline the strong corpus influence on the patterns efficiency and on their meaning. This influence confirms two of the hypotheses that motivated to define Cameleon as a support used in a supervised process: (1) patterns and relations must be adapted to each project; (2) human interpretation is required to decide how to report in the ontology the pieces of knowledge identified with patterns.

Abstract: CAMELEON is a symbolic layout system, suited for industrial designs, delivering layouts that can bear comparison with (orthogonal) manual layouts. The Technology Description Language (TDL), describing layout primitives and design rules, allows to customize the system to any technology. More complex primiltives, like S- or L-shaped transistors may be included in the stick diagram. Compaction is considered as a basic operation in the creation of stick diagrams: the designer can control compaction and receives feedback. An automatic technology conversion for all designed cells is obtained by modifying the TDL description. An electrical rules check is provided, and a fast circuit extraction module makes the link to simulation and verification tools.