Restructuring Sparse High Dimensional Data for Effective Retrieval

The task in text retrieval is to find the subset of a collection of documents relevant to a user's information request, usually expressed as a set of words. Classically, documents and queries are represented as vectors of word counts. In its simplest form, relevance is defined to be the dot product between a document and a query vector--a measure of the number of common terms. A central difficulty in text retrieval is that the presence or absence of a word is not sufficient to determine relevance to a query. Linear dimensionality reduction has been proposed as a technique for extracting underlying structure from the document collection. In some domains (such as vision) dimensionality reduction reduces computational complexity. In text retrieval it is more often used to improve retrieval performance. We propose an alternative and novel technique that produces sparse representations constructed from sets of highly-related words. Documents and queries are represented by their distance to these sets. and relevance is measured by the number of common clusters. This technique significantly improves retrieval performance, is efficient to compute and shares properties with the optimal linear projection operator and the independent components of documents

Leaching of Accumulated Soil Salinity Under Drip Irrigation

Conducted a reclamation leaching experiment in a drip-irrigated pistachio orchard south of Huron, California, during the winter of 2002-2003. The study was conducted to quantify the leaching water required to remove salts from the effective root zone of trees. This experiment tested a new reclamation leaching technique: multiple lines of low-flow drip tape were used to apply water to the area of salinity accumulation along a tree row. This new technique allows water to be applied where there is salt accumulation along the tree row, as opposed to putting water on the entire area of the field. Since reclamation leaching requires a relatively large depth of water, this technique offers the potential for significant water savings for reclamation leaching