IMPROVING ENCARTA SEARCH ENGINE PERFORMANCE BY MINING USER LOGS

2002 ◽  
Vol 16 (08) ◽  
pp. 1101-1116 ◽  
Author(s):  
CHARLES X. LING ◽  
JIANFENG GAO ◽  
HUAJIE ZHANG ◽  
WEINING QIAN ◽  
HONGJIANG ZHANG
Keyword(s):  
Data Mining ◽  
User Interface ◽  
Search Engine ◽  
Graphical User Interface ◽  
Engine Performance ◽  
Web Pages ◽  
Frequent User ◽  
Data Mining Approach ◽  
Query Patterns ◽  
User Queries

We propose a data-mining approach that produces generalized query patterns (with generalized keywords) from the raw user logs of the Microsoft Encarta search engine (). Those query patterns can act as cache of the search engine, improving its performance. The cache of the generalized query patterns is more advantageous than the cache of the most frequent user queries since our patterns are generalized, covering more queries and future queries — even those not previously asked. Our method is unique since query patterns discovered reflect the actual dynamic usage and user feedbacks of the search engine, rather than the syntactic linkage structure of web pages (as Google does). Simulation shows that such generalized query patterns improve search engine's overall speed considerably. The generalized query patterns, when viewed with a graphical user interface, are also helpful to web editors, who can easily discover topics in which users are mostly interested.

Traditional vs. Web Style Guides: How do they Differ?

1996 ◽  
Vol 40 (6) ◽  
pp. 365-369
Author(s):  
Julie A. Ratner ◽  
Eric Grose ◽  
Chris Forsythe
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Data Entry ◽  
Computer Interface ◽  
Web Pages ◽  
Human Computer Interface ◽  
Web Based ◽  
Information Display ◽  
Web Information ◽  
Style Guides

This paper describes a study in which Web style guides were characterized, compared to traditional human-computer interface (HCI) style guides, and evaluated against findings from HCI reviews of web pages and applications. Findings showed little consistency among the 21 Web style guides assessed, with 75% of recommendations appearing in only one style guide. While there was some overlap, only 20% of Web-relevant recommendations from traditional style guides were found in Web style guides. Web style guides emphasized common look and feel, information display, and navigation issues, with little mention of many issues prominent in traditional style guides such as help, message boxes, and data entry. This difference is reinforced by other results showing that Web style guides address Web information-only pages with much greater success than web-based control enabling features, like buttons and entry fields. It is concluded that while the WWW represents a unique graphical user interface (GUI) environment, development of Web style guides has been less rigorous, with issues associated with web-based control enabling features neglected.

scholarly journals Why-type Question to Query Reformulation for efficient Document Retrieval

2022 ◽  
Vol 12 (1) ◽  
pp. 0-0
Keyword(s):  
User Interface ◽  
Search Engine ◽  
Question Answering ◽  
Document Retrieval ◽  
Web Pages ◽  
Query Reformulation ◽  
Different Types ◽  
Why Questions ◽  
Google Search ◽  
Type Question

Understanding the actual need of user from a question is very crucial in non-factoid why-question answering as Why-questions are complex and involve ambiguity and redundancy in their understanding. The precise requirement is to determine the focus of question and reformulate them accordingly to retrieve expected answers to a question. The paper analyzes different types of why-questions and proposes an algorithm for each class to determine the focus and reformulate it into a query by appending focal terms and cue phrase ‘because’ with it. Further, a user interface is implemented which asks input why-question, applies different components of question , reformulates it and finally retrieve web pages by posing query to Google search engine. To measure the accuracy of the process, user feedback is taken which asks them to assign scoring from 1 to 10, on how relevant are the retrieved web pages according to their understanding. The results depict that maximum precision of 89% is achieved in Informational type why-questions and minimum of 48% in opinionated type why-questions.

Cluster Search Engine Results with Crowd Intelligence

2013 ◽  
Vol 284-287 ◽  
pp. 3375-3379
Author(s):  
Chun Hsiung Tseng ◽  
Fu Cheng Yang ◽  
Yu Ping Tseng ◽  
Yi Yun Chang
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Web Pages ◽  
Huge Amount ◽  
Search Results ◽  
Web Search Engines ◽  
Crowd Intelligence ◽  
User Queries

Most Web users today rely heavily on search engines to gather information. To achieve better search results, some algorithms such as PageRank have been developed. However, most Web search engines employ keyword-based search and thus have some natural weaknesses. Among these problems, a well-known one is that it is very difficult for search engines to infer semantics from user queries and returned results. Hence, despite of efforts of ranking search results, users may still have to navigate through a huge amount of Web pages to locate the desired resources. In this research, the researchers developed a clustering-based methodology to improve the performance of search engines. Instead of extracting features used for clustering from the returned documents, the proposed method extracts features from the delicious service, which is actually a tag provider service. By utilizing such information, the resulting system can benefit from crowd intelligence. The obtained information is then used for enhancing the performance of the ordinary k-means algorithm to achieve better clustering results.

Best Practices in Search User Interface Design

2002 ◽  
Vol 46 (5) ◽  
pp. 627-631
Author(s):  
Marc L. Resnick ◽  
Jennifer Bandos
Keyword(s):  
User Interface ◽  
Best Practices ◽  
Search Engine ◽  
Information Search ◽  
Interface Design ◽  
World Wide ◽  
Web Pages ◽  
Needed Information ◽  
The World ◽  
Search For Information

The Internet has become a powerful tool for information search and ecommerce. Millions of people use the World Wide Web on a regular basis and the number is increasing rapidly. For many common tasks, users first need to locate a Web site(s) containing needed information from among the estimated 4 trillion existing web pages. The most common method used to search for information is the search engine. However, even sophisticated users often have difficulty navigating through the complexity of search engine interfaces. Designing more effective and efficient search engines is contingent upon a significant improvement in the search user interface.

HOW TO USE CROP GROWTH MODEL WOFOST FOR FORECASTING GROWTH AND YIELD OF A CROP

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
LAL SINGH ◽  
PARMEET SINGH ◽  
RAIHANA HABIB KANTH ◽  
PURUSHOTAM SINGH ◽  
SABIA AKHTER ◽  
...  
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Input Data ◽  
Growth And Yield ◽  
Weather Data ◽  
Data Sets ◽  
Crop Growth Model ◽  
Control Center ◽  
Field Crops ◽  
Crop Calendar

WOFOST version 7.1.3 is a computer model that simulates the growth and production of annual field crops. All the run options are operational through a graphical user interface named WOFOST Control Center version 1.8 (WCC). WCC facilitates selecting the production level, and input data sets on crop, soil, weather, crop calendar, hydrological field conditions, soil fertility parameters and the output options. The files with crop, soil and weather data are explained, as well as the run files and the output files. A general overview is given of the development and the applications of the model. Its underlying concepts are discussed briefly.

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