Document understanding using data mining and machine learning techniques

With the explosive growth of the volume and complexity of document data (e.g., news, blogs, web pages), it has become a necessity to semantically understand documents and deliver meaningful information to users. Areas dealing with these problems are crossing data mining, information retrieval, and machine learning. For example, document clustering and summarization are two fundamental techniques for understanding document data and have attracted much attention in recent years. Given a collection of documents, document clustering aims to partition them into different groups to provide efficient document browsing and navigation mechanisms. One unrevealed area in document clustering is that how to generate meaningful interpretation for the each document cluster resulted from the clustering process. Document summarization is another effective technique for document understanding, which generates a summary by selecting sentences that deliver the major or topic-relevant information in the original documents. How to improve the automatic summarization performance and apply it to newly emerging problems are two valuable research directions. To assist people to capture the semantics of documents effectively and efficiently, the dissertation focuses on developing effective data mining and machine learning algorithms and systems for (1) integrating document clustering and summarization to obtain meaningful document clusters with summarized interpretation, (2) improving document summarization performance and building document understanding systems to solve real-world applications, and (3) summarizing the differences and evolution of multiple document sources.

Effect of Hydrologic Restoration on the Habitat of The Cape Sable Seaside Sparrow, Annual Report of 2002-2003

After developing field sampling protocols and making a series of consultations with investigators involved in research in CSSS habitat, we determined that vegetationhydrology interactions within this landscape are best sampled at a combination of scales. At the finer scale, we decided to sample at 100 m intervals along transects that cross the range of habitats present, and at the coarser scale, to conduct an extensive survey of vegetation at sites of known sparrow density dispersed throughout the range of the CSSS. We initiated sampling in the first week of January 2003 and continued it through the last week of May. During this period, we established 6 transects, one in each CSSS subpopulation, completed topographic survey along the Transects A, C, D, and F, and sampled herb and shrub stratum vegetation, soil depth and periphyton along Transects A, and at 179 census points. We also conducted topographic surveys and completed vegetation and soil depth sampling along two of five transects used by ENP researchers for monitoring long-term vegetation change in Taylor Slough. We analyzed the data by summarizing the compositional and structural measures and by using cluster analysis, ordination, weighted averaging regression, and weighted averaging calibration. The mean elevation of transects decreased from north to south, and Transect F had greater variation than other transects. We identified eight vegetation assemblages that can be grouped into two broad categories, ‘wet prairie’ and ‘marsh’. In the 2003 survey, wet prairies were most dominant in the northeastern sub-populations, and had shorter inferred-hydroperiod, higher species richness and shallower soils than marshes, which were common in Subpopulations A, D, and the southernmost regions of Sub-population B. Most of the sites at which birds were observed during 2001 or 2002 had an inferred-hydroperiod of 120-150 days, while no birds were observed at sites with an inferred-hydroperiod less than 120 days or more than 300 days. Management-induced water level changes in Taylor Slought during the 1980’s and 1990’s appeared to elicit parallel changes in vegetation. The results described in detail in the following pages serve as a basis for evaluating and modifying, if necessary, the sampling design and analytical techniques to be used in the next three years of the project.

Challenging ESL Students to Avoid Plagiarism and Properly Summarize and Cite Articles

Research shows that plagiarism is a problem not only for English language learners but also for students whose first language is English. With the Internet and ease of copying and pasting information into a word document, plagiarism in on the rise (Maslen, 2003). Oftentimes, students are not aware they are doing something wrong. American students come into college with the cultural conditioning of knowing (perhaps not fully grasping) American academic standards (Gu & Brooks, 2007). International students have the additional disadvantage of not knowing the conventions, traditions, and values held in academic discourse (Gu & Brooks, 2007). Within American academic circles, plagiarism is considered “one of the worst crimes” a student can commit (Wheeler, 2008). However, outside the United States, plagiarism is culturally acceptable; in fact a moral transgression would be to not copy and paste the words of an expert (Wheeler, 2008). Most of the students in English for Academic Purposes (EAP) at Miami-Dade College are planning on continuing their education once they finish the EAP program so it is essential that they are exposed to the issue of plagiarism. A number of faculty who teach in subject areas have complained that incoming students do not have the skills needed to succeed; these skills include how to cite sources and reference material. As a result of this, the focus of this action research project was on incorporating and explaining plagiarism and providing a number of writing opportunities throughout the semester.