Link Analysis Techniques Research Articles

Query based Personalization in Semantic Web Mining

To provide personalized support in on-line course resources system, a semantic web-based personalized learning service is proposed to enhance the learner's learning efficiency. When a personalization system relies solely on usage-based results, however, valuable information conceptually related to what is finally recommended may be missed. Moreover, the structural properties of the web site are often disregarded. In this Paper, we present a personalize Web search system, which can helps users to get the relevant web pages based on their selection from the domain list. In the first part of our work we present Semantic Web Personalization, a personalization system that integrates usage data with content semantics, expressed in ontology terms, in order to compute semantically enhanced navigational patterns and effectively generate useful recommendations. To the best of our knowledge, our proposed technique is the only semantic web personalization system that may be used by non-semantic web sites. In the second part of our work, we present a novel approach for enhancing the quality of recommendations based on the underlying structure of a web site. We introduce UPR (Usage-based Page Rank), a Page Rank-style algorithm that relies on the recorded usage data and link analysis techniques based on user interested domains and user query.

Unsupervised Action Classification Using Space-Time Link Analysis

We address the problem of unsupervised discovery of action classes in video data. Different from all existing methods thus far proposed for this task, we present a space-time link analysis approach which consistently matches or exceeds the performance of traditional unsupervised action categorization methods in various datasets. Our method is inspired by the recent success of link analysis techniques in the image domain. By applying these techniques in the space-time domain, we are able to naturally take into account the spatiotemporal relationships between the video features, while leveraging the power of graph matching for action classification. We present a comprehensive set of experiments demonstrating that our approach is capable of handling cluttered backgrounds, activities with subtle movements, and video data from moving cameras. State-of-the-art results are reported on standard datasets. We also demonstrate our method in a compelling surveillance application with the goal of avoiding fraud in retail stores.

Web site personalization based on link analysis and navigational patterns

The continuous growth in the size and use of the World Wide Web imposes new methods of design and development of online information services. The need for predicting the users' needs in order to improve the usability and user retention of a Web site is more than evident and can be addressed by personalizing it. Recommendation algorithms aim at proposing “next” pages to users based on their current visit and past users' navigational patterns. In the vast majority of related algorithms, however, only the usage data is used to produce recommendations, disregarding the structural properties of the Web graph. Thus important—in terms of PageRank authority score—pages may be underrated. In this work, we present UPR , a PageRank-style algorithm which combines usage data and link analysis techniques for assigning probabilities to Web pages based on their importance in the Web site's navigational graph. We propose the application of a localized version of UPR ( l-UPR ) to personalized navigational subgraphs for online Web page ranking and recommendation. Moreover, we propose a hybrid probabilistic predictive model based on Markov models and link analysis for assigning prior probabilities in a hybrid probabilistic model. We prove, through experimentation, that this approach results in more objective and representative predictions than the ones produced from the pure usage-based approaches.

Emergency Department Communication Links and Patterns

We characterize and describe the communication links and patterns between and within emergency department (ED) practitioner types. This is a prospective, observational study of emergency physician and nursing staff communication patterns in an academic ED using link analysis techniques. Twenty ED staff members were observed in the pediatric and adult acute areas of the ED, including attending physicians, residents, nurses, and charge nurses. Data were recorded for each communication event, including duration, mode, partner, location, and interruptions. Because this study was intended to focus on professionally related communication between staff, social interactions and direct patient interactions were excluded. Frequency percentage and duration were calculated for each measure, and link analysis graphs were prepared to assist in interpretation of the data. One thousand six hundred sixty-five total communication events were recorded during a total of 39 hours 12 minutes of observation. Face-to-face communication was the most common mode. Communication links and patterns were described and graphically represented using a link analysis technique. Communication gaps were found between ambulance providers and the providers who would ultimately take care of the patient during their ED stay. Attending physicians communicated often despite caring for separate patients, and the charge nurse seemed to be the hub for communication, linking ED personnel with non-ED staff. In the adult area, interruption rates ranged from 6.9 per hour (attending physician) to 0.5 per hour (bedside nurse), and in the pediatric area they ranged from 3.6 per hour (attending physician) to 0.3 (bedside nurse). Distinct patterns are identified. These results will be helpful in designing future communication adjuncts in the ED.

Using link analysis technique with a modified shortest-path algorithm to fight money laundering

Effective link analysis techniques are needed to help law enforcement and intelligence agencies fight money laundering. This paper presents a link analysis technique that uses a modified shortest-path algorithms to identify the strongest association paths between entities in a money laundering network. Based on two-tree Dijkstra and Priority-First-Search (PFS) algorithm, a modified algorithm is presented. To apply the algorithm, a network representation transformation is made first.

Time-Aware Authority Ranking

The link structure of the web is analyzed to measure the authority of pages, which can be taken into account for ranking query results. Due to the enormous dynamics of the web, with millions of pages created, updated, deleted, and linked to every day, temporal aspects of web pages and links are crucial factors for their evaluation. Users are interested in important pages (i.e., pages with high authority score) but are equally interested in the recency of information. Time—and thus the freshness of web content and link structure—emanates as a factor that should be taken into account in link analysis when computing the importance of a page. So far only minor effort has been spent on the integration of temporal aspects into link-analysis techniques. In this paper we introduce T-Rank Light and T-Rank, two link-analysis approaches that take into account the temporal aspects freshness (i.e., timestamps of most recent updates) and activity (i.e., update rates) of pages and links. Experimental results show that T-Rank Light and T-Rank can produce better rankings of web pages.

Fighting organized crimes: using shortest-path algorithms to identify associations in criminal networks

Effective and efficient link analysis techniques are needed to help law enforcement and intelligence agencies fight organized crimes such as narcotics violation, terrorism, and kidnapping. In this paper, we propose a link analysis technique that uses shortest-path algorithms, priority-first-search (PFS) and two-tree PFS, to identify the strongest association paths between entities in a criminal network. To evaluate effectiveness, we compared the PFS algorithms with crime investigators' typical association-search approach, as represented by a modified breadth-first-search (BFS). Our domain expert considered the association paths identified by PFS algorithms to be useful about 70% of the time, whereas the modified BFS algorithm's precision rates were only 30% for a kidnapping network and 16.7% for a narcotics network. Efficiency of the two-tree PFS was better for a small, dense kidnapping network, and the PFS was better for the large, sparse narcotics network.

A TIME AND MOTION STUDY OF THE ANAESTHETIST'S INTRAOPERATIVE TIME

A time and motion study was made of anaesthetists during 32 surgical procedures. Thirteen activities performed by the anaesthetist were defined for the study. Time and event data were recorded electronically and analysed by digital computer. Activity and link analysis techniques were used to analyse the data. Only 25% of intraoperative time was spent observing the physiological state of the patient. Seventy-five percent was spent in secondary or indirect activities. Direct observation of the patient was least in the middle of the procedure when the anaesthetist was performing secondary activities. Prudent use of personnel, machines, or both, to perform activities not requiring full medical knowledge and training should increase the anaesthetist's ability to focus full attention on the state of the patient and may improve patient care.

Minimizing Cost and Effort in Performing a Link Analysis

For several years link analysis techniques have proven to be very useful tools in human-machine systems planning. The primary drawback found in the application of these methodologies is that the time and manual effort required is often prohibitive in terms of the cost of analysis. Within the context of this paper methods for reducing the time required to perform a link analysis are introduced. The application of a relationship chart and the attendant procedures are shown to provide a systematic approach to the establishment of the link values for a human-machine system. A computer program is employed to develop a block plan layout. The feasibility and computational efficiency of these techniques are demonstrated through an example problem.