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The advent of the Web reshaped the way in which humans memorize information, arguably unlike any other technological advance of the last decades. Rather than remembering the information itself, people are primed to find the needed information through Web s ...
Information retrieval (IR) systems such as search engines are important for people to find what they need among the tremendous amount of data available in their organization or on the Internet. These IR systems enable users to search in a large data collec ...
The continuous increase, witnessed in the last decade, of both the amount of available data and the areas of application of machine learning, has lead to a demand for both learning and planning algorithms that are capable of handling large-scale problems. ...
We present a novel approach to automatic macroaction discovery and its application to a complex goal-planning task. The problem of macro-action discovery is framed as one of multiple change point detection and is addressed with the help of the Dynamic Prog ...
Internet ranking algorithms play a crucial role in information technologies and numerical analysis due to their efficiency in high dimensions and wide range of possible applications, including scientometrics and systemic risk in finance (SinkRank, DebtRank ...
We present new techniques to analyze natural local search algorithms for several variants of the max-sum diversification problem which, in its most basic form, is as follows: given an n-point set X subset of R-d and an integer k, select k points in X so th ...
Selection and aggregation of ranking criteria became an important topic in information retrieval as search is getting more specialized and as volume of electronically available information grows. In this context, document ranking has undergone a shift from ...
As sensors continue to proliferate, the capabilities of effectively querying not only sensor data but also its metadata becomes important in a wide range of applications. This paper demonstrates a search system that utilizes various techniques and tools fo ...
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The discovery of web documents about certain topics is an important task for web-based applications including web document retrieval, opinion mining and knowledge extraction. In this paper, we propose an agent-based focused crawling framework able to retri ...
This paper addresses the problem of building concise, diverse and relevant lists of documents, which can be recommended to the participants of a conversation to fulfill their information needs without distracting them. These lists are retrieved periodicall ...
