Investigating query bursts in a web search engine

نویسندگان

  • Ilija Subasic
  • Carlos Castillo
چکیده

The Internet has become for many the most important medium for staying informed about current news events. Some events cause heightened interest on a topic, which in turn yields a higher frequency of the search queries related to it. These queries are going through a “query burst”. In this paper we examine the behavior of search engine users during a query burst, compared to before and after the burst. We are interested in how this behavior changes, and how it affects other stake-holders in web search. We analyze one year of web-search and news-search logs, looking at query bursts from multiple perspectives. First, we adopt the perspective of search engine users, describing changes in their effort and interest while searching. Second, we adopt the perspective of news providers by comparing web search and news search query bursts. Third, we look at the burst from the perspective of content providers. We study the conditions under which content providers can “ride” a wave of increased interest on a topic, and obtain a share of the user’s increased attention. We do so by identifying the class of queries that can be considered as an opportunity for content providers that are “late-comers” for a query, in the sense of not being among the first to write about its topic. We also present a simple model for predicting the click share content providers could obtain if they decide to provide content about these queries.

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

Query Architecture Expansion in Web Using Fuzzy Multi Domain Ontology

Due to the increasing web, there are many challenges to establish a general framework for data mining and retrieving structured data from the Web. Creating an ontology is a step towards solving this problem. The ontology raises the main entity and the concept of any data in data mining. In this paper, we tried to propose a method for applying the "meaning" of the search system, But the problem ...

متن کامل

Query expansion based on relevance feedback and latent semantic analysis

Web search engines are one of the most popular tools on the Internet which are widely-used by expert and novice users. Constructing an adequate query which represents the best specification of users’ information need to the search engine is an important concern of web users. Query expansion is a way to reduce this concern and increase user satisfaction. In this paper, a new method of query expa...

متن کامل

A New Hybrid Method for Web Pages Ranking in Search Engines

There are many algorithms for optimizing the search engine results, ranking takes place according to one or more parameters such as; Backward Links, Forward Links, Content, click through rate and etc. The quality and performance of these algorithms depend on the listed parameters. The ranking is one of the most important components of the search engine that represents the degree of the vitality...

متن کامل

Towards Supporting Exploratory Search over the Arabic Web Content: The Case of ArabXplore

Due to the huge amount of data published on the Web, the Web search process has become more difficult, and it is sometimes hard to get the expected results, especially when the users are less certain about their information needs. Several efforts have been proposed to support exploratory search on the web by using query expansion, faceted search, or supplementary information extracted from exte...

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

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:
  • Web Intelligence and Agent Systems

دوره 11  شماره 

صفحات  -

تاریخ انتشار 2013