Text retrieval by using k-word proximity search

When we search from a huge amount of documents, we often specify several keywords and use conjunctive queries to narrow the result of the search. Though the searched documents contain all keywords, positions of the keywords are usually not considered. As the result, the search result contains some meaningless documents. It is therefore effective to rank documents according to proximity of keywords in the documents. This ranking is regarded as a kind of text data mining. We propose two algorithms for finding documents in which all given keywords appear in neighboring places. One is based on the plane-sweep algorithm and the other is based on a divide-and-conquer approach. Both algorithms run in O(n log n) time where n is the number of occurrences of given keywords. We run the plane-sweep algorithm on a large collection of HTML files and verify its effectiveness