The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Highly regular, modular, and cascadable design of cellular automata-based pattern classifier
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special issue on system-level interconnect prediction
ACM Transactions on Internet Technology (TOIT)
Using web structure for classifying and describing web pages
Proceedings of the 11th international conference on World Wide Web
Mining the Web's Link Structure
Computer
Theory and application of cellular automata for pattern classification
Fundamenta Informaticae - Special issue on cellular automata
Nonlinear CA Based Design of Test Set Generator Targeting Pseudo-Random Pattern Resistant Faults
ATS '04 Proceedings of the 13th Asian Test Symposium
Theory of Self-Reproducing Automata
Theory of Self-Reproducing Automata
Generation of SMACA and its application in web services
PaCT'07 Proceedings of the 9th international conference on Parallel Computing Technologies
Search engine indexing storage optimisation using Hamming distance
International Journal of Intelligent Information and Database Systems
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Web search engine uses indexing for management of web-pages in a mannered way. Web-pages are well distributed within the database of server. Both forward and inverted indexing is employed to tackle web-pages as a part of its functional design. This indexing mechanism helps in retrieving data from the database based on user query. In this paper, an efficient solution to handle the indexing problem is proposed with the introduction of non-linear single cycle multiple attractor cellular automata (SMACA). This paper also reports an analysis on SMACA using rule vector graph (RVG). This work simultaneously shows generation of SMACA by using specific rule sequence. Searching mechanism is done with O(n) complexity. SMACA provides an implicit memory to store the patterns. Search operation to identify the class of a pattern out of several classes boils down to running a cellular automata (CA) for one time step. This demands storage of the CA rule vector (RV) and the seed values. SMACA is based on sound theoretical foundation of CA technology.