Browsing by Subject "World Wide Web."

Now showing 1 - 3 of 3

Open Access
Characteristics of Web-based textual communications
(2012) Küçükyılmaz, Tayfun
In this thesis, we analyze different aspects of Web-based textual communications and argue that all such communications share some common properties. In order to provide practical evidence for the validity of this argument, we focus on two common properties by examining these properties on various types of Web-based textual communications data. These properties are: All Web-based communications contain features attributable to their author and reciever; and all Web-based communications exhibit similar heavy tailed distributional properties. In order to provide practical proof for the validity of our claims, we provide three practical, real life research problems and exploit the proposed common properties of Web-based textual communications to find practical solutions to these problems. In this work, we first provide a feature-based result caching framework for real life search engines. To this end, we mined attributes from user queries in order to classify queries and estimate a quality metric for giving admission and eviction decisions for the query result cache. Second, we analyzed messages of an online chat server in order to predict user and mesage attributes. Our results show that several user- and message-based attributes can be predicted with significant occuracy using both chat message- and writing-style based features of the chat users. Third, we provide a parallel framework for in-memory construction of term partitioned inverted indexes. In this work, in order to minimize the total communication time between processors, we provide a bucketing scheme that is based on term-based distributional properties of Web page contents.
Open Access
Replacement problem in Web caching
(2002) Çakıroğlu, Seda
Open Access
A template-independent content extraction approach for new web pages
(2012) Yeniçağ, Ahmet
News web pages contain additional elements such as advertisements, hyperlinks, and reader comments. These elements make the extraction of news contents a challenging task. Current news content extraction (NCE) methods are usually template-dependent. They require regular maintenance, since news providers frequently change their web page templates. Therefore, there is a need for NCE methods that extract news contents accurately without depending on web page templates. In this thesis, a template-independent News content EXTraction approach, called N-EXT, is introduced. It rst parses a web page into its blocks according to the HTML tags. Then, it examines all blocks to detect the one that contains the major part of the news content. For this purpose, it assigns weights to the blocks by considering both their textual sizes and similarities to the news title. For quantifying the importance of these two weight components, we use the k-fold cross validation approach; and for assessing the impact of di erent possible similarity measures, we use a one-way Analysis of Variance (ANOVA) with a Sche e comparison. The block with the highest weight is considered as the news block. Our approach eliminates the sentences in the news block that are not related to the news content by considering similarities of sentences to the news block. Finally, it also examines other blocks to detect the rest of the news content. The experimental results show the accuracy and robustness of our method by using two test collections whose web pages are obtained from several di erent news websites.