The semantic snake charmer search engine: A tool to facilitate data science in high-tech industry domains

The booming popularity of data science is also affecting high-tech industries. However, since these usually have different core competencies - building cyber-physical systems rather than e.g. machine learning or data mining algorithms - delving into data science by domain experts such as system engineers or architects might be more cumbersome...

The Semantic Snake Charmer Search Engine: A Tool to Facilitate Data Science in High-tech Industry Domains

The booming popularity of data science is also affecting high-tech industries. However, since these usually have different core competencies — building cyber-physical systems rather than e.g. machine learning or data mining algorithms — delving into data science by domain experts such as system engineers or architects might be more cumbersome...

Large scale track analysis for wide area motion imagery surveillance

Wide Area Motion Imagery (WAMI) enables image based surveillance of areas that can cover multiple square kilometers. Interpreting and analyzing information from such sources, becomes increasingly time consuming as more data is added from newly developed methods for information extraction. Captured from a moving Unmanned Aerial Vehicle (UAV), the...

Interactive detection of incrementally learned concepts in images with ranking and semantic query interpretation

The number of networked cameras is growing exponentially. Multiple applications in different domains result in an increasing need to search semantically over video sensor data. In this paper, we present the GOOSE demonstrator, which is a real-time general-purpose search engine that allows users to pose natural language queries to retrieve...

A search engine for retrieval and inspection of events with 48 human actions in realistic videos

The contribution of this paper is a search engine that recognizes and describes 48 human actions in realistic videos. The core algorithms have been published recently, from the early visual processing (Bouma, 2012), discriminative recognition (Burghouts, 2012) and textual description (Hankmann, 2012) of 48 human actions. We summarize the key...

Personalization in professional academic search

In this paper, we investigated how academic search can profit from personalization by incorporating query history and background knowledge in the ranking of the results. We implemented both techniques in a language modelling framework, using the Indri search engine. For our experiments, we used the iSearch data collection, a large corpus of...

Using Wikipedia's category structure for entity search

In this paper we investigate how the category structure of Wikipedia can be exploited for Entity Ranking. In the last decade, theWeb has not only grown in size, but also changed its character, due to collaborative content creation and an increasing amount of structure. Current Search Engines find Web pages rather than information or knowledge,...

Using query logs and click data to create improved descriptions

Logfles of search engines are a promising resource for data mining, since they provide raw data associated to users and web documents. In this paper we focus on the latter as- pect and explore how the information in logfles could be used to improve document descriptions. A pilot experiment demonstrated that document descriptors extracted from...

The MediaMill TRECVID 2006 semantic video search engine

In this paper we describe our TRECVID 2006 experiments. The MediaMill team participated in two tasks: concept detection and search. For concept detection we use the MediaMill Challenge as experimental platform. The MediaMill Challenge divides the generic video indexing problem into a visual-only, textual-only, early fusion, late fusion, and...

A language modeling approach to the Text Retrieval Conference

In this paper we present the language modeling approach to information retrieval as a toolbox to systematically combine information from different sources. Four TREC subtasks (Ad Hoc, Entry Page, Adaptive Filtering and Cross-language) are used to illustrate the application of language models to different information retrieval problems.

The importance of prior probabilities for entry page search

An important class of searches on the world-wide-web has the goal to find an entry page (homepage) of an organisation. Entry page search is quite different from Ad Hoc search. Indeed a plain Ad Hoc system performs disappointingly. We explored three non-content features of web pages: page length, number of incoming links and URL form. Especially...