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Detecting word substitutions in text

Detecting word substitutions in text

... As recent experience with popular web sites such as MySpace.com indicates, the electronic commu- nication facilitated by those sites may provide leads to detecting and thwarting violent plots [2]. Since much of ... See full document

13

Ambiguity in Semantically Related Word Substitutions: an investigation in historical Bible translations

Ambiguity in Semantically Related Word Substitutions: an investigation in historical Bible translations

... a word as a substitution candidate for para-phrasal reuse increases with the number of the senses of a ...compare word substitutions to another sense annotated dataset and to define the ambiguity by ... See full document

6

Detecting Multi Word Expressions Improves Word Sense Disambiguation

Detecting Multi Word Expressions Improves Word Sense Disambiguation

... TALP Word Sense Dis- ambiguation system in (Castillo et ...the text, assigned a part-of- speech tag, and finally determined a lemma for each stemmable ... See full document

5

Detecting Concealed Information in Text and Speech

Detecting Concealed Information in Text and Speech

... tion (Snoek et al., 2012) to tune the hyperparam- eters. It was used to maximize the F1 scores on the development set, based on various hyperpa- rameters including learning rate, number of hid- den layers of MLP, the ... See full document

11

Detecting Text in Natural Images

Detecting Text in Natural Images

... Mail text image spam can be easily detected, reactionary and fraud words can be easily filtered by using content- based filtering ...technique. Text region detection in scene images are taken with laptops, ... See full document

6

Deep contextualized word representations for detecting sarcasm and irony

Deep contextualized word representations for detecting sarcasm and irony

... each word-level embedding contains con- textual information from their ...Billion Word Benchmark which contains about 800M tokens of news crawl data from WMT 2011 (Chelba et ... See full document

6

Detecting Missing Hyphens in Learner Text

Detecting Missing Hyphens in Learner Text

... (3) My father like play basketball with me. In this paper, we propose a classifier-based approach to automatically detecting missing hyphen errors. The goal of our system is to detect missing hyphen errors and ... See full document

6

Detecting Speculations and their Scopes in Scientific Text

Detecting Speculations and their Scopes in Scientific Text

... as Word Sense Disambiguation (WSD) and ...tags, word stems, surrounding and co-occurring words, and dependency relationships have been successfully used in WSD (Montoyo et ...in text sum- marization ... See full document

10

Detecting Expressions of Blame or Praise in Text

Detecting Expressions of Blame or Praise in Text

... We started to explore the use of the Path Model of Blame (Malle et al, 2014) for the detection of blame/praise from text. As we are not concerned with the identification of the degree of blame but the existence of ... See full document

6

Automatic Detecting/Correcting Errors in Chinese Text by an Approximate Word Matching Algorithm

Automatic Detecting/Correcting Errors in Chinese Text by an Approximate Word Matching Algorithm

... [r] ... See full document

7

Certified Robustness to Adversarial Word Substitutions

Certified Robustness to Adversarial Word Substitutions

... one word can allow or disallow changes to other ...same word can be substituted multiple times, leading to semantic ...allowed substitutions relative to the original sentence x, and disallow re- ... See full document

14

Is Sentence Compression an NLG task?

Is Sentence Compression an NLG task?

... only word deletions are allowed – no substitutions or insertions – and therefore no paraphrases; (2) the word order is ...as word deletion ... See full document

8

Detecting Visual Text

Detecting Visual Text

... each node that has connections with known (seeds) or automatically labeled nodes, previously exploited to learn hyponymy relations from the web (Kozareva et al., 2008). Intuitively, in-degree captures the pop- ularity of ... See full document

11

Towards Detecting Counter considerations in Text

Towards Detecting Counter considerations in Text

... tional text), where the notion of exception to an ar- gument plays a role, but its function is quite different from the perspective-switching that we discuss ...using word lists and numbers (for identifying ... See full document

6

Contribution of Word Length in Non-word Error Distribution of Punjabi Typed Text

Contribution of Word Length in Non-word Error Distribution of Punjabi Typed Text

... In English Kukich[1] analyzed over 2000 error types in a corpus of TDIL conversations and found that over 63% of the errors occurred in words of length 2,3,4 characters. According to our results the maximum of the ... See full document

5

Department of ECE, Adhiyamaan College of Engineering, Hosur, Tamilnadu, India

Department of ECE, Adhiyamaan College of Engineering, Hosur, Tamilnadu, India

... The above image is an example of how the user’s utterances matches with an intent in an agent. Whenever a user speaks or text, its checks all of the intents in the agent. The intent matches will be triggered to ... See full document

10

Low Cost DTMF Controlled Landmine Detection Rover

Low Cost DTMF Controlled Landmine Detection Rover

... and reason for a large number of soldier casualties. While governments around the world have been working towards restricting the production and sales of these landmines, they remain a major threat to soldiers around the ... See full document

6

Indexing and Searching Document Collections using Lucene

Indexing and Searching Document Collections using Lucene

... The upper left part of the GUI lists the choice of desired text fields namely title, abstract, description and audience. The logical relation between different fields is “OR”. In the example shown in Figure 3.y, ... See full document

47

Contextual Spelling Correction Using Latent Semantic Analysis

Contextual Spelling Correction Using Latent Semantic Analysis

... The similarity between this text passage vector and the confusion word vectors can be used to predict the most likely word given the context or text in which it will appear.. Separate co[r] ... See full document

8

Finding Word Substitutions Using a Distributional Similarity Baseline and Immediate Context Overlap

Finding Word Substitutions Using a Distributional Similarity Baseline and Immediate Context Overlap

... one word can substitute the other in frequent immediate contexts, we have the basis to believe that entailment is possible in at least one common sense of the words – while if substitution is impossible or rare, ... See full document

9

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