Text Processing

This book constitutes the refereed post-conference proceedings of a Workshop focussing on Text Processing, held at the Forum for Information Retrieval Evaluation, FIRE 2016, in Kolkata, India, in December 2016. 16 full papers have been selected for inclusion in the book out of 19 submissions. The papers refer to the following seven tracks: Consumer Health Information Search (CHIS), Detecting Paraphrases in Indian Languages (DPIL), Information Extraction from Microblogs Posted during Disasters, Persian Plagiarism Detection (PersianPlagDet), Personality Recognition in SOurce COde (PR-SOCO), Shared Task on Mixed Script Information Retrieval (MSIR), and Shared Task on Code Mix Entity Extraction in Indian Languages (CMEE-IL).

Includes supplementary material: sn.pub/extras

Inhalt
PAN at FIRE: Overview of the PR-SOCO Track on Personality Recognition in SOurce Code.- Microblog Retrieval during Disasters: Comparative Evaluation of IR Methodologies.- Overview of the Mixed Script Information Retrieval (MSIR) at FIRE-2016.- From Vector Space Models to Vector Space Models of Semantics.- Algorithms and Corpora for Persian Plagiarism Detection: Overview of PAN at FIRE 2016.- Predicting Type of Obfuscation to Enhance Text Alignment Algorithms.- A Fast Multi-Level Plagiarism Detection Method based on Document Embedding Representation.- Plagiarism Detection Based on a Novel Trie-Based Approach.- Using Local Text Similarity in Pairwise Document Analysis for Monolingual Plagiarism Detection.- Shared Task on Detecting Paraphrases in Indian Languages (DPIL): An Overview.- Anuj@DPIL-FIRE2016: A Novel Paraphrase Detection Method in Hindi Language using Machine Learning.- Learning to Detect Paraphrases in Indian Languages.- Sentence Paraphrase Detection Using Classification Models.- Feature Engineering and Characterization of Classifiers for Consumer Health Information Search.- Identification of Relevance and Support for Consumer Health Information.- Entity Extraction of Hindi-English and Tamil-English Code-Mixed Social Media Text.