14904013
Support concept-based multimedia information retrieval: a knowledge management approach
Identified as an important management concept five years ago (Garner 1999), knowledge management (KM) aims to enable organizations to capture, organize, and access their intellectual assets. This paper proposes a prototype system that applies a knowledge management approach to support concept-based multimedia information retrieval by integrating various information analysis and image processing techniques. The proposed system uses geographical information as its testbed and aims to provide flexibility to users in terms of specifying their information needs and to facilitate parallel extraction of information in different formats (i.e., text, image). Our testbed selection is based not only on the fact that geographical information has become an important resource supporting organization decision making, but also on the diversity of its information media and the fuzziness of geo-spatial queries. We hope that the proposed system will improve the accessibility of geographical information in different media and provide an example of integrating various information and multimedia techniques to support concept-based cross-media information retrieval.
770502
Visualizing the archive of a computer mediated communication process
The archive of computer-mediated communication (CMC) process contains knowledge shared and information about participants' behavior patterns. However, most CMC systems focus only on organizing the content of discussions. We propose to demo a prototype system that integrates a social visualization technique with existing information analysis technologies to graphically summarize both the content and behavior of a CMC process.
16961887
Newsmap: a knowledge map for online news
Information technology has made possible the capture and accessing of a large number of data and knowledge bases, which in turn has brought about the problem of information overload. Text mining to turn textual information into knowledge has become a very active research area, but much of the research remains restricted to the English language. Due to the differences in linguistic characteristics and methods of natural language processing, many existing text analysis approaches have yet to be shown to be useful for the Chinese language. This research focuses on the automatic generation of a hierarchical knowledge map NewsMap, based on online Chinese news, particularly the finance and health sections. Whether in print or online, news still represents one important knowledge source that people produce and consume on a daily basis. The hierarchical knowledge map can be used as a tool for browsing business intelligence and medical knowledge hidden in news articles. In order to assess the quality of the map, an empirical study was conducted which shows that the categories of the hierarchical knowledge map generated by NewsMap are better than those generated by regular news readers, both in terms of recall and precision, on the sub-level categories but not on the top-level categories. NewsMap employs an improved interface combining a ID alphabetical hierarchical list and a 2D Self-Organizing Map (SOM) island display. Another empirical study compared the two visualization displays and found that users' performances can be improved by taking advantage of the visual cues of the 2D SOM display.
30023273
MedTextus: an intelligent web-based medical meta-search system
We propose to demonstrate a web-based prototype system that integrates the meta-search approach with existing information analysis and visualization technologies to facilitate concept-based searching behavior over the medical domain. The system distinguishes itself from other meta-search engines through two features. It incorporates the co-occurrence analysis and existing ontology to understand user's query. It also utilizes the self-organizing map (SOM) to categorize and visualize search results.
9274167
Communication-Garden System: Visualizing a computer-mediated communication process
Archives of computer-mediated communication (CMC) could be valuable organizational resources. Most CMC archive systems focus on presenting one of the three aspects of a CMC community: discussion content, participants' behavior, or social networks among participants. Very few CMC archive systems support the easy integration of these three aspects. This paper thus describes two-phase research to propose an automatic approach that facilitates users' integrated understanding of discussion content and behavior of CMC participants. We validated the approach through the development and evaluation of a prototype system, the Communication-Garden system.
12630328
Creating a large-scale content-based airphoto image digital library
This paper describes a content-based image retrieval digital library that supports geographical image retrieval over a testbed of 800 aerial photographs, each 25 megabytes in size. In addition, this paper also introduces a methodology to evaluate the performance of the algorithms in the prototype system. There are two major contributions: we suggest an approach that incorporates various image processing techniques including Gabor filters, image enhancement and image compression, as well as information analysis techniques such as the self-organizing map (SOM) into an effective large-scale geographical image retrieval system. We present two experiments that evaluate the performance of the Gabor-filter-extracted features along with the corresponding similarity measure against that of human perception, addressing the lack of studies in assessing the consistency between an image representation algorithm or an image categorization method and human mental model.
12614266
SVision: A Network Host-Centered Anomaly Visualization Technique
We proposed a technique merged from a combination of both anomaly and graphical methods, for intrusion detection. The network is pictured as a community of hosts that exchange messages among themselves. Our aim is to graphically highlight those hosts that represent a possible threat for the network, so that a network administrator will be able to further explore the anomaly and decide upon the responses that are appropriate. We choose to test our view against the DARPA 99 intrusion detection and evaluation dataset since it provides labels which we can use to monitor our system. Experiments show our visualization technique as a possible alternative for detection of network intrusions, in particular Denial of Service (DoS) and Distributed-DoS attacks such as Ping Of Death, UDP storm, SSH Process Table, and Smurf, to name a few.
4515160
Alert Correlation for Extracting Attack Strategies
Alert correlation is an important technique for managing large the volume of intrusion alerts that are raised by heterogenous Intrusion Detection Systems (IDSs). The recent trend of research in this area is towards extracting attack strategies from raw intrusion alerts. It is generally believed that pure intrusion detection no longer can satisfy the security needs of organizations. Intrusion response and prevention are now becoming crucially important for protecting the network and minimizing damage. Knowing the real security situation of a network and the strategies used by the attackers enables network administrators to launches appropriate response to stop attacks and prevent them from escalating. This is also the primary goal of using alert correlation technique. However, most of the current alert correlation techniques only focus on clustering inter-connected alerts into different groups without further analyzing the strategies of the attackers. Some techniques for extracting attack strategies have been proposed in recent years, but they normally require defining a larger number of rules. This paper focuses on developing a new alert correlation technique that can help to automatically extract attack strategies from a large volume of intrusion alerts, without specific prior knowledge about these alerts. The proposed approach is based on two different neural network approaches, namely, Multilayer Perceptron (MLP) and Support Vector Machine (SVM). The probabilistic output of these two methods is used to determine with which previous alerts this current alert should be correlated. This suggests the causal relationship of two alerts, which is helpful for constructing attack scenarios. One of the distinguishing feature of the proposed technique is that an Alert Correlation Matrix (ACM) is used to store correlation strengthes of any two types of alerts. ACM is updated in the training process, and the information (correlation strength) is then used for extracting high level attack strategies.
5048240
Current state of the art, challenges and future directions for audio watermarking
Transparent data embedding algorithms embed binary streams in host multimedia signals. The embedded data is perceptually inaudible to maintain the quality of the source data. The embedded data can add features to the host multimedia signal or provide copyright protection. We review developments and requirements in transparent data embedding techniques for audio signals. We describe our latest audio embedding algorithm and include experimental results indicating robustness to low bit rate MPEG-Layer 3, AAC, and Dolby AC-3 coding. We conclude with a discussion of future research directions.
26786201
Conditional Dempster-Shafer Theory for Uncertain Knowledge Updating
This paper presents a theory called conditional Dempster-Shafer theory (CDS) for uncertain knowledge updating. In this theory, a prioriknowledge about the value attained by an uncertain variable is modeled by a fuzzy measure and the evidence about the underlying uncertain variable is modeled by the Dempster-Shafer belief measure. Two operations in CDS are discussed in this paper, the conditioned combination rule and conditioning rule, which deal with evidence combining and knowledge updating, respectively. We show that conditioned combination rule and conditioning rule in CDS satisfy the property of Bayesian parallel combination.
6858621
A management strategy for distributed data in collaborative design
This paper presents a distributed data management strategy for collaborative design, which supports the data exchange pattern based on any fine-grained data as well as that based on traditional file service. Data are represented using XML and their exchange is achieved through the publishing and subscription mechanism among individual participants. It is also shown in this paper that how the data replication mechanism, which supports both synchronous and asynchronous mechanism, propagates updates among data copies to provide consistent views of data among many computers, in which the rule-based approach is used to resolve conflict. Based on this strategy, a research prototype system of collaborative design has been implemented and tested in the design of auto-body welding lines.