Antti Tuominen

A Scalable Topic-Based Open Source Search Engine

Site-based or topic-specific search engines work with mixed success because of the general difficulty of the information retrieval task, and the lack of good link information to allow authorities to be identified. We are advocating an open source approach to the problem due to its scope and need for software components. We have adopted a topic-based search engine because it represents the next generation of capability. This paper outlines our scalable system for site-based or topic-specific search, and demonstrates the developing system on a small 250,000 document collection of EU and UN web pages.

Image Similarity: From Syntax to Weak Semantics Using Multimodal Features with Application to Multimedia Retrieval

Measuring image similarity is an important task for various multimedia applications. Similarity can be defined at two levels: at the syntactic (lower, context-free) level and at the semantic (higher, contextual) level. As long as one deals with the syntactic level, defining and measuring similarity is a relatively straightforward task, but as soon as one starts dealing with the semantic similarity, the task becomes very difficult. We examine the use of very simple syntactic image features combined with other multimodal features to derive a similarity measure that captures the weak semantics of an image. We test and further use this similarity measure to do video retrieval.

Image similarity: from syntax to weak semantics

Measuring image similarity is an important task for various multimedia applications. Similarity can be defined at two levels: at the syntactic (lower, context-free) level and at the semantic (higher, contextual) level. As long as one deals with the syntactic level, defining and measuring similarity is a relatively straightforward task, but as soon as one starts dealing with the semantic similarity, the task becomes very difficult. We examine the use of simple readily available syntactic image features combined with other multimodal features to derive a similarity measure that captures the weak semantics of an image. The weak semantics can be seen as an intermediate step between low level image understanding and full semantic image understanding. We investigate the use of single modalities alone and see how the combination of modalities affect the similarity measures. We also test the measure on multimedia retrieval task on a tv series data, even though the motivation is in understanding how different modalities relate to each other.