Detecting intent shift is fundamental for learning users’ behaviors and applying their experiences. In this paper, we propose a search-query-log based system to predict users’ intent shifts. We begin with selecting sessions in search query logs for training, extracting features from the selected sessions, and clustering sessions of similar intent. The resulting intent clusters are used to predi...

We present a fast and accurate method to compose images delivered by a quadocular document scanner into a global consistent image. The Shift Detection by Restoration (SDR) approach is used to overcome document deformations. Our method outperforms state of the art panoramic image approaches and is able to work within one second on standard hardware.

Split cuts are among the most important and well-understood cuts for general mixed-integer programs. In this paper we consider some recent generalizations of split cuts and compare their relative strength. More precisely, we compare the elementary closures of split, cross, crooked cross and general multi-branch split cuts as well as cuts obtained from multi-row and basic relaxations. We present...

We present a procedure for proving the validity of rst-order formulas in the presence of decision procedures for an interpreted subset of the language. The procedure is designed to be practical: formulas can have large complex boolean structure, and include structure sharing in the form of let-expressions. The decision procedures are only required to decide the unsatissability of sets of litera...

This paper presents first results of automatic semantic shift detection in Slovene tweets. We use word embeddings to compare the semantic behaviour of common words frequently occurring in a reference corpus of Slovene with their behaviour on Twitter. Words with the highest model distance between the corpora are considered as semantic shift candidates. They are manually analysed and classified i...

Domain adaptation, the problem of adapting a natural language processing system trained in one domain to perform well in a different domain, has received significant attention. This paper addresses an important problem for deployed systems that has received little attention – detecting when such adaptation is needed by a system operating in the wild, i.e., performing classification over a strea...

Analysis of IC technology trends indicates that Iddq testing may be approaching its limits of applicability. The new concept of the current signature may expand this limit under the condition that an appropriate current-signature-based test methodology is developed. This paper is a first step toward such a goal. It is focused on current signature step detection in a noisy test environment. Appl...

A common problem of existing methods for regime shift detection is their poor performance at the ends of time-series. Consequently, shifts in environmental and biological indices are usually detected long after their actual appearance. A recently introduced method based on sequential t-test analysis of regime shifts (STARS) treats all incoming data in real time, signals the possibility of a reg...

In a mobile business collaboration environment, frequent itemsets analysis will discover the noticeable associated events and data to provide important information of user behaviors. Many algorithms have been proposed for mining frequent itemsets over data streams. However, in many practical situations where the data arrival rate is very high, continuous mining the data sets within a sliding wi...