Related papers: Effective Personalized Web Mining by Utilizing The…
Training and refreshing a web-scale Question Answering (QA) system for a multi-lingual commercial search engine often requires a huge amount of training examples. One principled idea is to mine implicit relevance feedback from user behavior…
Indexing the Web is becoming a laborious task for search engines as the Web exponentially grows in size and distribution. Presently, the most effective known approach to overcome this problem is the use of focused crawlers. A focused…
Conflicts of interest often arise between data sources and their users regarding how the users' information needs should be interpreted by the data source. For example, an online product search might be biased towards presenting certain…
Most online services (Google, Facebook etc.) operate by providing a service to users for free, and in return they collect and monetize personal information (PI) of the users. This operational model is inherently economic, as the "good"…
In the search engine of Google, the PageRank algorithm plays a crucial role in ranking the search results. The algorithm quantifies the importance of each web page based on the link structure of the web. We first provide an overview of the…
Web search is among the most ubiquitous online activities, commonly used to acquire new knowledge and to satisfy learning-related objectives through informational search sessions. The importance of learning as an outcome of web search has…
Traditional approaches to ranking in web search follow the paradigm of rank-by-score: a learned function gives each query-URL combination an absolute score and URLs are ranked according to this score. This paradigm ensures that if the score…
This paper presents a link analysis approach for identifying privileged documents by constructing a network of human entities derived from email header metadata. Entities are classified as either counsel or non-counsel based on a predefined…
Web search engines apply a variety of ranking signals to achieve user satisfaction, i.e., results pages that provide the best-possible results to the user. While these ranking signals implicitly consider credibility (e.g., by measuring…
It is shown that personalization of web content can be advantageously viewed as a form of partial evaluation --- a technique well known in the programming languages community. The basic idea is to model a recommendation space as a program,…
The application of process mining for unstructured data might significantly elevate novel insights into disciplines where unstructured data is a common data format. To efficiently analyze unstructured data by process mining and to convey…
In e-commerce websites, web mining web page recommendation technology has been widely used. However, recommendation solutions often cannot meet the actual application needs of online shopping users. To address this problem, this paper…
In the practical work of websites popularization, analysis of their efficiency and downloading it is of key importance to take into account web-ratings data. The main indicators of website traffic include the number of unique hosts from…
Online learning to rank is a sequential decision-making problem where in each round the learning agent chooses a list of items and receives feedback in the form of clicks from the user. Many sample-efficient algorithms have been proposed…
Profiling users for the purpose of targeted advertisements or other kinds of personalization is very popular on the internet. But besides the benefits of individually tailored news feeds and shopping recommendation research has shown that…
This paper explores how to analyze empirically a network of website visitors from several countries in the world. While exploring this huge network of website visitors worldwide, this paper shows an empirical data analysis with a…
Web search engines arguably form the most popular data-driven systems in contemporary society. They wield a considerable power by functioning as gatekeepers of the Web, with most user journeys on the Web beginning with them. Starting from…
Ranking is at the core of Information Retrieval. Classic ranking optimization studies often treat ranking as a sorting problem with the assumption that the best performance of ranking would be achieved if we rank items according to their…
Some of the main ranking features of today's search engines reflect result popularity and are based on ranking models, such as PageRank, implicit feedback aggregation, and more. While such features yield satisfactory results for a wide…
Performing effective preference-based data retrieval requires detailed and preferentially meaningful structurized information about the current user as well as the items under consideration. A common problem is that representations of items…