This work presents a study to bridge topic modeling and personalized search. A probabilistic topic model is used to extract topics from user search history. These topics can be se...
In the KL divergence framework, the extended language modeling approach has a critical problem estimating a query model, which is the probabilistic model that encodes user’s inf...
In this paper, we propose a new object detection method that does not need a learning mechanism. Given a hand-drawn model as a query, we can detect and locate objects that are sim...
Chih-Wen Su, Mark Liao, Yu-Ming Liang, Hsiao-Rong ...
Abstract. Most of the recent work on adaptive processing and continuous querying of data streams assume that data objects come in the form of tuples, thus relying on the relational...
Michael Gertz, Quinn Hart, Carlos Rueda, Shefali S...
We use Wikipedia articles to semantically inform the generation of query models. To this end, we apply supervised machine learning to automatically link queries to Wikipedia artic...
We describe a subsystem of a content-based image retrieval (CBIR) environment that supports a user in the definition of image similarity. Out of a single image or a set of query i...
Query-by-example is the most popular query model for today’s image retrieval systems. A typical query image contains not only relevant objects (e.g., Eiffel Tower), but also ir...
The window query model is widely used in data stream management systems where the focus of a continuous query is limited to a set of the most recent tuples. In this dissertation, ...
We extend the binary search technique to searching in trees. We consider two models of queries: questions about vertices and questions about edges. We present a general approach t...
Genetic algorithms (GAs) have long been used for large join query optimization (LJQO). Previous work takes all queries as based on one granularity to optimize GAs and compares the...