Source evaluation and summaries

Most books and articles display this prominently, but you may have to look harder for the date on a website or web article. This tool does not use word frequency, does not need training or Source evaluation and summaries of any kind and works by generating ideograms that represent the meaning of each sentence and then summarizes using two user-supplied parameters: Submodular functions as generic tools for summarization[ edit ] The idea of a submodular set function has recently emerged as a powerful modeling tool for various summarization problems.

A word that appears multiple times throughout a text may have many different co-occurring neighbors. For Web sites, do most of the links on the page work? Then the sentences can be ranked with regard to their similarity to this centroid sentence.

Since this method simply ranks the individual vertices, we need a way to threshold or produce a limited number of keyphrases. Pay particular attention to the last part of the domain name for example, the edu in the URL www. Each article is likely to have many similar sentences, and you would only want to include distinct ideas in the summary.

Preparation Guide for Competitive Source Selection Proposal Evaluation Reports (PER)

Thus, to get ranked highly and placed in a summary, a sentence must be similar to many sentences that are in turn also similar to many other sentences. This discount cannot be combined with the Completion Scholarship for Maryland community college students or the Pennsylvania Completion Scholarship.

Depending on the different literature and the definition of key terms, words or phrases, keyword extraction is a highly related theme. Similarly, the facility location problem is a special case of submodular functions.

The authors found that adjectives and nouns were the best to include. The main difficulty in supervised extractive summarization is that the known summaries must be manually created by extracting sentences so the sentences in an original training document can be labeled as "in summary" or "not in summary".

A keyphrase extractor might select "Army Corps of Engineers", "President Bush", "New Orleans", and "defective flood-control pumps" as keyphrases. Instead of trying to learn explicit features that characterize keyphrases, the TextRank algorithm [4] exploits the structure of the text itself to determine keyphrases that appear "central" to the text in the same way that PageRank selects important Web pages.

Matches between the proposed keyphrases and the known keyphrases can be checked after stemming or applying some other text normalization.

Is the resource completed or under construction? To address this issue, LexRank applies a heuristic post-processing step that builds up a summary by adding sentences in rank order, but discards any sentences that are too similar to ones already placed in the summary.

Evaluating Sources

While some work has been done in abstractive summarization creating an abstract synopsis like that of a humanthe majority of summarization systems are extractive selecting a subset of sentences to place in a summary.

The vertices should correspond to what we want to rank. Moreover, several important combinatorial optimization problems occur as special instances of submodular optimization.

Although articles in newspapers and popular magazines can help with introductory research, since they help you to learn the basics of a topic, you will probably want to use scholarly resources for more advanced research.

You are given a piece of text, such as a journal article, and you must produce a list of keywords or key[phrase]s that capture the primary topics discussed in the text [2]. TextRank uses continuous similarity scores as weights.Because summaries are a high-level overview, put the source’s information into your own words, rather than quoting the original source.

Doing so will help increase the flow of your summary and ensure your voice as the author comes through. In any case, what the evaluation methods need as an input, is a set of summaries to serve as gold standards and a set of automatic summaries.

Moreover, they all perform a quantitative evaluation with regard to different similarity metrics. Evaluating Sources Use credible research sources to strengthen your arguments.

Sometimes your instructor will require you to incorporate certain types of resources into your research, but for other assignments, you will be looking for sources on your own.

Automatic summarization

Based on the information provided in the evaluation, the team determined that the student’s instructional needs are significantly different from expectations in all areas of concern.

In addition, the team determined that Jimmy has information processing needs in a variety of settings. Evaluation Summary Report. Source Evaluation Checklist.

Use this "Evaluating Web Resources" checklist from Cornell University Library's Introduction to Research tutorial to evaluate the information sources you discover as a result of performing a search. Check the items in each of the following categories: Purpose. What is the purpose or motivation for the source?

Source: Stetson (), p. Resources Guide and Example. Communicating and Reporting on an Evaluation: This guide from Catholic Relief Services and American Red Cross provides a detailed explanation and example (see above)of an Executive Summary.

Evaluation Executive Summaries & Reports.

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Source evaluation and summaries
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