Method, system, and apparatus for automatic keyword recommendation based on individual user behavior
Original Publication Date: 2008-Aug-26
Included in the Prior Art Database: 2008-Aug-26
The present invention provides a computer implemented method of refining search result by keyword recommendation to filter unrelated items in search result, and the recommendation is based on both user’s input and analysis result of documents or results clicked by user in subsequent actions.
Method, system, and apparatus for automatic keywordrecommendation based on individual user behavior
BRIEF DESCRIPTION OF THE DRAWINGS
Fig. 1-a, 1-b and 1-c illustrates how the method interacts with users via a search sample.
Fig. 2 describes how the presented invention works.
Fig. 3 depicts a software architecture in which methods and systems may be implemented according to the present invention for user selection driven search query optimization.
DETAILED DESCRIPTION OF THE INVENTION
Apple - Education - Price Lists
K-12 and Higher Education Apple Professional Development, Curriculum Development, Product Training, and Technical Training Price List, 05/13/08 ...
3G iPhone catalyst behind Apple price target hike to US
Follow the markets in real time with FP Trading Desk, your up- to-the-minute look at Bay Street and beyond from Financial Post.
Shenzhen: apple price increased dramatically in Nanchang wholesale
In the Shenzhen Nanchang wholesale market, a fruit retailer has mentioned that the apple price has increased by 50% this year due to the low production ...
iPhone revenue sharing pushing analysts to rethink Apple price targets
2007/11/9 ... One item that's been giving analysts trouble is how to predict the stock price from Apple now that it is getting revenue over time from the ...
Green Apple Fruit - Compare Prices, Reviews and Buy at NexTag ...
Green Apple Fruit - 243 results like the Kappus Soaps - Green Apple - Fruit Soap (oval) 4.2 oz, Scitec ISO Fruit Delite Green Apple,2 lb, ...
In Fig.1-a, the initial search action begin from 101. User inputs the keywords in input box 101, then click search button 102, and search results will be shown by pages. For the sample shown in Fig. 1-a. User is interested inthe apple price, then he input keywords "Apple price", but the results contains several kinds of "Apple" price. In fact, he/she
which is related to his/her needs.
In Fig. 1-b, a recommendation message 105 is shown just after user's first two clicks. In this message, keywords "Apple price fruit" is recommended to user and this recommendation is based on the analysis result of search items 103 and 104
system will automatically analysis it together
After the analysis on documents 103 and 104, the system finds out that the two documents have another keyword "fruit" in common besides "Apple price", so new keywords "Apple price fruit" is recommended. User can follow the recommendation or ignore it. If user chooses the recommendation, then he/she clicks recommendation 106, and Fig. 1-c will be shown.
In Fig. 1-c, input box 107 is replaced with keywords "Apple price fruit", and the search results returned 108 are all fruit "Apple" price related which is user really wants, and then time can be saved from finding needed information page by page....