Study on the Web Information Search Prediction Algorithm

2011 ◽  
pp. 434-438
Author(s):  
Zhong-Sheng Wang ◽  
Mei Cao
Keyword(s):  
Information Search ◽  
Prediction Algorithm ◽  
Web Information ◽  
The Web

WEBYACHT: A CONCEPT-BASED SEARCH TOOL FOR WWW

1999 ◽  
Vol 08 (02) ◽  
pp. 137-156 ◽  
Author(s):  
CHING-CHI HSU ◽  
CHIA-HUI CHANG
Keyword(s):  
Information Search ◽  
Relevance Feedback ◽  
Web Search ◽  
Automatic Assessment ◽  
Feedback Mechanisms ◽  
Document Ranking ◽  
Search Results ◽  
Web Information ◽  
Search Tool ◽  
The Web

This paper describes a Web information search tool called WebYacht. The goal of WebYacht is to solve the problem of imprecise search results in current Web search engines. Due to incomplete information given by users and the diversified information published on the Web, conventional document ranking based on an automatic assessment of document relevance to the query may not be the best approach when little information is given as in most cases. In order to clarify the ambiguity of the short queries given by users, WebYacht adopts cluster-based browsing model as well as relevance feedback to facilitate Web information search. The idea is to have users give two to three times more feedback in the same amount of time that would be required to give feedback for conventional feedback mechanisms. With the assistance of cluster-based representation provided by WebYacht, a lot of browsing labor can be reduced. In this paper, we explain the techniques used in the design of WebYacht and compare the performances of feedback interface designs and to conventional similarity ranking search results.

Web Information Retrieval

2011 ◽  
pp. 218-252 ◽  
Author(s):  
Guillaume Cabanac ◽  
Max Chevalier ◽  
Claude Chrisment ◽  
Christine Julien ◽  
Chantal Soulé-Dupuy ◽  
...  
Keyword(s):  
Social Networks ◽  
Information Retrieval ◽  
Search Engine ◽  
Information Search ◽  
Information Needs ◽  
Information Source ◽  
Web Information Retrieval ◽  
Web Information ◽  
The Social ◽  
The Web

Nowadays, the Web has become the most queried information source. To solve their information needs, individuals can use different types of tools or services like a search engine, for instance. Due to the high amount of information and the diversity of human factors, searching for information requires patience, perseverance, and sometimes luck. To help individuals during this task, search assistants feature adaptive techniques aiming at personalizing retrieved information. Moreover, thanks to the “new Web” (the Web 2.0), personal search assistants are evolving, using social techniques (social networks, sharing-based methods). Let us enter into the Social Web, where everyone collaborates with others in providing their experience, their expertise. This chapter introduces search assistants and underlines their evolution toward Social Information Search Assistants.

scholarly journals Query Recommendation Using Hybrid Query Relevance

2018 ◽  
Vol 10 (11) ◽  
pp. 112
Author(s):  
Jialu Xu ◽  
Feiyue Ye
Keyword(s):  
Information Retrieval ◽  
Information Search ◽  
Search Engines ◽  
Web Search ◽  
Superior Performance ◽  
Recommendation Algorithm ◽  
Web Information ◽  
Query Recommendation

With the explosion of web information, search engines have become main tools in information retrieval. However, most queries submitted in web search are ambiguous and multifaceted. Understanding the queries and mining query intention is critical for search engines. In this paper, we present a novel query recommendation algorithm by combining query information and URL information which can get wide and accurate query relevance. The calculation of query relevance is based on query information by query co-concurrence and query embedding vector. Adding the ranking to query-URL pairs can calculate the strength between query and URL more precisely. Empirical experiments are performed based on AOL log. The results demonstrate the effectiveness of our proposed query recommendation algorithm, which achieves superior performance compared to other algorithms.

scholarly journals Intelligent Web Information Extraction Model for Agricultural Product Quality and Safety System

2021 ◽  
pp. 99-110
Author(s):  
Mohammad Ali Tofigh ◽  
◽  
◽  
Zhendong Mu
Keyword(s):  
Information Extraction ◽  
Product Quality ◽  
Hot Spot ◽  
Safety System ◽  
Agricultural Product ◽  
Quality And Safety ◽  
Web Information Extraction ◽  
Web Information ◽  
Product Quality And Safety ◽  
The Web

With the development of society, people pay more and more attention to the safety of food, and relevant laws and policies are gradually introduced and being improved. The research and development of agricultural product quality and safety system has become a research hot spot, and how to obtain the Web information of the system effectively and quickly is the focus of the research, so it is essential to carry out the intelligent extraction of Web information for agricultural product quality and safety system. The purpose of this paper is to solve the problem of how to efficiently extract the Web information of the agricultural product quality and safety system. By studying the Web information extraction methods of various systems, the paper makes a detailed analysis and research on how to realize the efficient and intelligent extraction of the Web information of the agricultural product quality and safety system. This paper analyzes in detail all kinds of template information extraction algorithms used at present, and systematically discusses a set of schemes that can automatically extract the Web information of agricultural product quality and safety system according to the template. The research results show that the proposed scheme is a dynamically extensible information extraction system, which can independently implement dynamic configuration templates according to different requirements without changing the code. Compared with the general way, the Web information extraction speed of agricultural product quality safety system is increased by 25%, the accuracy is increased by 12%, and the recall rate is increased by 30%.

A Knowledge-Based Web Information System for the Fusion of Distributed Classifers

2004 ◽  
pp. 268-304 ◽  
Author(s):  
Grigorios Tsoumakas ◽  
Nick Bassiliades ◽  
Ioannis Vlahavas
Keyword(s):  
Information System ◽  
Distributed Databases ◽  
Semantic Heterogeneity ◽  
Knowledge Based ◽  
Classifier Selection ◽  
Web Information System ◽  
Web Information ◽  
Geographically Distributed ◽  
Fusion Of Classifiers ◽  
The Web

This chapter presents the design and development of WebDisC, a knowledge-based web information system for the fusion of classifiers induced at geographically distributed databases. The main features of our system are: (i) a declarative rule language for classifier selection that allows the combination of syntactically heterogeneous distributed classifiers; (ii) a variety of standard methods for fusing the output of distributed classifiers; (iii) a new approach for clustering classifiers in order to deal with the semantic heterogeneity of distributed classifiers, detect their interesting similarities and differences, and enhance their fusion; and (iv) an architecture based on the Web services paradigm that utilizes the open and scalable standards of XML and SOAP.

Web Information Extraction via Web Views

2004 ◽  
pp. 227-267
Author(s):  
Wee Keong Ng ◽  
Zehua Liu ◽  
Zhao Li ◽  
Ee Peng Lim
Keyword(s):  
Information Extraction ◽  
Data Model ◽  
Information Source ◽  
Extraction Process ◽  
Web Pages ◽  
Efficient Manner ◽  
Web Information Extraction ◽  
Web Information ◽  
Definition Of ◽  
The Web

With the explosion of information on the Web, traditional ways of browsing and keyword searching of information over web pages no longer satisfy the demanding needs of web surfers. Web information extraction has emerged as an important research area that aims to automatically extract information from target web pages and convert them into a structured format for further processing. The main issues involved in the extraction process include: (1) the definition of a suitable extraction language; (2) the definition of a data model representing the web information source; (3) the generation of the data model, given a target source; and (4) the extraction and presentation of information according to a given data model. In this chapter, we discuss the challenges of these issues and the approaches that current research activities have taken to revolve these issues. We propose several classification schemes to classify existing approaches of information extraction from different perspectives. Among the existing works, we focus on the Wiccap system — a software system that enables ordinary end-users to obtain information of interest in a simple and efficient manner by constructing personalized web views of information sources.

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