Preface
Since its inception in 2008, the FIRE community has grown in stature and has
played a prominant role in conducting Information Retrieval Evaluation in
South Asia. FIRE 2016 workshop proceedings is the biggest volume in history
of FIRE so far, with a diverse participation of 64 teams.

We hosted the following 7 tracks in 2016.

     Consumer Health Information Search (CHIS) : This track aims to
      investigate complex health information search in scenarios where
      users search for health information with more than just a single correct
      answer, and look for multiple perspectives from diverse sources both
      from medical research and from real world patient narratives.

     Detecting Paraphrases in Indian Languages (DPIL) : In this track,
      given a pair of sentences in the same language, participants are asked
      to detect the semantic equivalence between the sentences. The shared
      task was proposed for four Indian languages namely, Tamil, Malayalam,
      Hindi, and Punjabi.

     Information Extraction from Microblogs Posted during
      Disasters : This track offered IR challenges on tweets collected during
      a disaster event (here, Nepal earthquake 2015) for broad queries like
      resource need, resource identification etc.

     Persian Plagiarism Detection (PersianPlagDet) : This track was
      on detecting plagiarism in documents written in Persian (subtask on
      text alignment) as well as to provide corpora that contain cases of
      plagiarism in Persian (subtask on corpus construction).

     Personality Recognition in SOurce COde (PR-SOCO) : This track
      addressed the problem of predicting an author’s personality traits from
      her source code. That is, given a set of source codes written in Java by
      students who answered a personality test, participants had to predict
      their personality traits.

     Shared Task on Mixed Script Information Retrieval (MSIR) : This
      track hosted two subtasks - (a) Subtask-1 was on classifying code-
      mixed cross-script question; b) Subtask-2 was on information retrieval
      of Hindi-English code-mixed tweets.
      Shared Task on Code Mix Entity Extraction in Indian Languages
       (CMEE-IL) : The objective of the task was to encourage research in
       entity recognition and extraction for the code mixed social media text.
       This track aimed at identification of the various entities such as person
       names, organization names, movie names, location names in a given
       tweet. The tweets were written in Roman script and has code mix,
       where an Indian Language is mixed with English.

FIRE 2016 saw the introduction of three new tracks Consumer Health
Information Search, Detecting Paraphrases in Indian Language and
Information Extraction from Microblogs Posted during Disasters. Other tracks
have evolved over some of the previous FIRE iterations offering various
facets of a central problem.

We express our heartfelt gratitude to the track organizers for taking pains in
organizing these interesting tracks and thus presenting exciting research
problems to the community.

FIRE data has been used frequently for empirical studies across the
community in information access. Papers in reputed journals like ACM TALIP,
IPM, IR etc. and conferences like SIGIR, CIKM etc. have regularly cited FIRE
data. The download of FIRE data has increased considerably over the past
few years.

We look forward to continuing this endeavour in future. We will consider this
effort worthy if readers find the datasets and experiments reported in this
volume useful.




                                                         Prasenjit Majumder
                                                               Mandar Mitra
                                                                 Parth Mehta
                                                        Jainisha Sankhavara
                                                         Kripabandhu Ghosh