On a New Model and Algorithm to Estimate Geographical Similarity between Document and Query in Gir System

نویسنده

  • Xing Lin
چکیده

The usage of single geographical footprint model in existing Geographical Information Retrieval (GIR) system will cause many problems like overestimation or underestimation of the geographical scopes for documents to search. To be honest, the single geographical footprint model is not applicable in modern GIR system although it is simple, fast and widely applied today. In order to improve the quality of answers given to a spatial query, a new model as well as a dedicated algorithm will be proposed to study the geographical information attached to documents. Besides, a dedicated algorithm based on network graph, which is inspired by the Google PageRank and Bayesian network theory, is also invented to estimate the geographical similarity between document

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

مدل جدیدی برای جستجوی عبارت بر اساس کمینه جابه‌جایی وزن‌دار

Finding high-quality web pages is one of the most important tasks of search engines. The relevance between the documents found and the query searched depends on the user observation and increases the complexity of ranking algorithms. The other issue is that users often explore just the first 10 to 20 results while millions of pages related to a query may exist. So search engines have to use sui...

متن کامل

خوشه‌بندی اسناد مبتنی بر آنتولوژی و رویکرد فازی

Data mining, also known as knowledge discovery in database, is the process to discover unknown knowledge from a large amount of data. Text mining is to apply data mining techniques to extract knowledge from unstructured text. Text clustering is one of important techniques of text mining, which is the unsupervised classification of similar documents into different groups. The most important step...

متن کامل

RRLUFF: Ranking function based on Reinforcement Learning using User Feedback and Web Document Features

Principal aim of a search engine is to provide the sorted results according to user’s requirements. To achieve this aim, it employs ranking methods to rank the web documents based on their significance and relevance to user query. The novelty of this paper is to provide user feedback-based ranking algorithm using reinforcement learning. The proposed algorithm is called RRLUFF, in which the rank...

متن کامل

GeoVSM: An Integrated Retrieval Model for Geographic Information

Geographical information exists in multiple forms such as cartographical maps, images, and texts. Effective retrieval systems for geographical information are currently studied by both geospatial information scientists and library/information scientists. The two groups take quite different approaches which have rarely been explicitly compared and connected. This paper discusses the advantages a...

متن کامل

Web pages ranking algorithm based on reinforcement learning and user feedback

The main challenge of a search engine is ranking web documents to provide the best response to a user`s query. Despite the huge number of the extracted results for user`s query, only a small number of the first results are examined by users; therefore, the insertion of the related results in the first ranks is of great importance. In this paper, a ranking algorithm based on the reinforcement le...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008