Extracting gene pathway relations using a hybrid grammar: the Arizona Relation Parser

The amount of deception taking place via electronic textbased communication is increasing. Research has sought to automatically detect deception by analyzing the text from the communicator. However, the deceptive intent of the communication partner is being ignored. We compare the text from subjects who are trying to deceive each other, subjects trying to deceive truth tellers, subjects telling the truth to truth tellers, and subjects telling the truth to deceivers. We hypothesize that despite the intent of the partner, deceitful text will cluster closest to deceitful text. We cluster each of the four conditions using the text content. The cluster algorithm placed subjects trying to deceive each other closest to subjects telling the truth to each other. In this analysis, the language that led subjects to choose the same outcomes had a stronger effect than the language tied to being deceitful or truthful.

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“…Each of these four groups of chat content was processed by our content tagging computer program [25]. The program assigned all the tags.…”

Section: Processing the Textmentioning

confidence: 99%

When Deceitful Chats Look Truthful

McDonald

Boyle

Anderson

2016

Journal of Computer Information Systems

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“…There are a lot of similar text mining systems that can extract gene relation information from biomedical literature, such as STRING-IE system in EMBL project (Saric et al, 2005), Arizona Relation Parser System (McDonald et. al., 2004 Second, we extend the CASS Grammar provided by STRING-IE system (Saric et al, 2005).…”

Section: Research Contribution In Text Mining Biomedical Literature Smentioning

confidence: 99%

Text mining biomedical literature for constructing gene regulatory networks

Song

Chen

2009

Interdiscip Sci Comput Life Sci

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“…However, since many CMC users choose common English words as their screen names, word sense disambiguation methods need to be applied to differentiate common usages of a word with the use of a word as a screen name. Our HIC algorithm makes use of WordNet (Miller, 1990), which has already been widely used in word sense identification (Voorhees, 1993;Resnek, 1995), to identify the meaning of words, and a POS tagger (McDonald, Chen, Su, & Marshall, 2004) …”

Section: Hic Algorithm: System Feature Matchmentioning

confidence: 99%

A hybrid approach to Web forum interactional coherence analysis

Abbasi

Chen

2008

J. Am. Soc. Inf. Sci.

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Despite the rapid growth of text-based computer-mediated communication (CMC), its limitations have rendered the media highly incoherent. This poses problems for content analysis of online discourse archives. Interactional coherence analysis (ICA) attempts to accurately identify and construct CMC interaction networks. In this study, we propose the Hybrid Interactional Coherence (HIC) algorithm for identification of web forum interaction. HIC utilizes a bevy of system and linguistic features, including message header information, quotations, direct address, and lexical relations. Furthermore, several similarity-based methods including a Lexical Match Algorithm (LMA) and a sliding window method are utilized to account for interactional idiosyncrasies. Experiments results on two web forums revealed that the proposed HIC algorithm significantly outperformed comparison techniques in terms of precision, recall, and F-measure at both the forum and thread levels. Additionally, an example was used to illustrate how the improved ICA results can facilitate enhanced social network and role analysis capabilities.

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Extracting gene pathway relations using a hybrid grammar: the Arizona Relation Parser

Abstract: Relations extracted from over 600 000 PubMed abstracts are available for retrieval and visualization at http://econport.arizona.edu:8080/NetVis/index.html.

Cited by 44 publications

References 11 publications

When Deceitful Chats Look Truthful

When Deceitful Chats Look Truthful

Text mining biomedical literature for constructing gene regulatory networks

A hybrid approach to Web forum interactional coherence analysis

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