[PDF] Top 20 How to Evaluate Opinionated Keyphrase Extraction?

... to evaluate our automatic meth- ods in two different ...of keyphrase extraction, which is not realistic in the case of machine trans- lation or summarization (only one output is offered for each ... See full document

... extracting opinionated phrases are quite similar to that of extracting stan- dard (most of the time scientific) keyphrases, fea- tures of the standard setting were applied in this task as ...for keyphrase ... See full document

... Many academic journals ask their authors to provide a list of about five to fifteen keywords, to appear on the first page of each article. Since these key words are often phrases of two or more words, we prefer to call ... See full document

... they evaluate their method indirectly through a summa- rization task, and to our knowledge there are no published experiments using other centrality mea- sures for keyphrase ...of keyphrase ... See full document

... training set (Frank et al., 1999; Kim et al., 2012). Second, as Frank et al. (1999) noted: authors do not always choose keyphrases that best describe the content of their paper, but they may choose phrases to slant their ... See full document

... for keyphrase extraction our proposed methods utilizes both the doc- ument’s text and label information for the task of extracting label specific ...We evaluate and report the quality of the ... See full document

... experimentally evaluate difer- ent crowdsourced answer aggregation strategies and validate their performances against expert anno- tations to evaluate the quality of our ... See full document

... the keyphrase extraction task is conducted separately without interactions for each ...better evaluate and extract salient keyphrases from each ... See full document

... Keyphrases can provide highly condensed and valuable information that allows users to quickly acquire the main ideas. The task of automatically extracting them have received considerable attention in recent decades. ... See full document

... similar documents stored on the user’s desktop and then determine keywords for these docu- ments. They evaluate different term scoring techniques, such as term and document fre- quency, lexical dispersion, ... See full document

... Redundancy errors occur when a system correctly iden- tifies a candidate as a keyphrase, but at the same time out- puts a semantically equivalent candidate (e.g., its alias) as a keyphrase. This type of ... See full document

... keyword Extraction methods which provide the main contents of a given ...documents. Keyphrase extraction method aims to select a set of terms like bigram, trigram and N-gram words from a given ... See full document

... on how a specific document is related. Keyphrase extraction systems are becoming increasingly vital in extracting quality ...Existing keyphrase extraction systems, that employed the ... See full document

... TextRank and 10 for SingleRank. As well as their window size, they differ in the weighting of the graph: TextRank has an unweighted graph and SingleRank has a graph weighted with the number of co-occurrences between the ... See full document

... Experiments have been performed on two dif- ferent data sets. One is a collection of scientif- ic publication abstracts, while the other consists of news articles with human-annotated keyphras- es. Experimental results ... See full document

... As shown in Figure 2, users largely prefer the keyphrase extracted with EmbedRank++ (λ = 0.5). This is a major finding, as it is in contradic- tion with the F-scores given in Table 2. If the result is confirmed by ... See full document

... In this paper, we propose a new keyphrase extrac- tion method, called Salience Rank. It improves upon the Topical PageRank algorithm by Liu et al. (2010) and the Single Topical PageRank algorithm by Sterckx et al. ... See full document

... prospective keyphrase node, results in a higher fraction of features prop- agating from such nodes being included to its neighboring ...cal keyphrase neighborhoods of highly weighted keyphrases, making the ... See full document

... dation is recursively computed based on the im- portance of the words making the recommendation. Keyphrase extraction can be divided into two steps. First, a weighted graph is constructed from the set of ... See full document

... In order to use the Wiki50 corpus for testing only, we automatically generated a train database for the CRF trainer. The train set consists of 5,000 randomly selected Wikipedia pages and we ig- nored those containing ... See full document