Multi-dimensional navigation method of search results based on dimension tags

Abstract

The invention discloses a search-result multi-dimensional navigating method on the basis of dimension labels, and a dimension hierarchical tree is generated by utilizing the dimension information of a document. The search-result multi-dimensional navigating method comprises the following steps of requiring the document to have a plurality of different dimension labels (such as conceptions, time, places and characters), wherein each dimension has a hierarchical structure; interacting with a user through the dimension hierarchical tree in a filtering or browsing mode; showing the distribution and the summary of the document on each dimension in an interaction result to the user through the dimension hierarchical tree and a document list. The search-result multi-dimensional navigating method can be used for expanding a result set on dimensions by layer, checking distributed information and document summaries and helping as well as quickening the user to acquire required knowledge from mass results and has broad prospects in the fields of knowledge discovery, result analysis and showing and data mining.

Description

Technical field [0001] The invention relates to the field of data mining, in particular to a method for multi-dimensional navigation of search results based on dimensional tags. Background technique [0002] Search engines generally display search results by ranking based on relevance. With the rapid increase in the amount of data, its drawbacks have become increasingly prominent: for example, the sorting of search results is not accurate; users need to spend more time to obtain the desired information; some statistical information about the search results cannot be obtained. For example, using existing search engines, it is difficult for users to obtain the most concentrated sub-field of computer field papers, and at the same time obtain the specific distribution of papers in this sub-field in terms of time, location and author. This demand is in practical applications Very important. [0003] Existing search engines have made a lot of improvements in accuracy, using priority an...

AI Technical Summary

Problems solved by technology

The method of clustering or clustering based on eigenvectors requires a lot of calculations, and when the dimension of the eigenvectors is large, the clustering effect will become worse; the method of taking correlation or correlation ranking with priority is still a The single-dimensional presentation method cannot provide multi-dimensional presentation functions; the method of layered display in a folding manner is used to display the current data node and its lower-level child nodes in concentric circles of different diameters, which is more intuitive visually, but it is impossible to view data on the same level distribution, lack of macroscopic

In addition, the above methods only provide one viewing mode, and the ability to interact with users is relatively weak

Images