Web Documents are of vital importance as they provide information from basic to the core requirements of users. The web documents have similarity based on the content and information represented. The key information in the web documents can be analyzed and can be represented as features. This leads to the importance of using similarity measures for categorizing and representing the web documents back to the users. This is a vital challenge as the documents could be clustered and represented in multiple dimensions for retrieval. This paper performs a complete survey of different techniques that are available for retrieving the web documents. The paper also presents investigations of the different performance parameters available for measuring the performance of results. The paper also presents research directions for using soft computing techniques for web document retrieval.

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Clustering Feature Vector Neural Network Index Dimension Filters Probability