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Tokenization and proper noun recognition for information retrieval

F.M. Barcala, J. Vilares, M.A. Alonso, J. Grana, M. Vilares
Proceedings. 13th International Workshop on Database and Expert Systems Applications  
phenomena, as well as for pre-tagging tasks such as proper noun recognition.  ...  We also show the results of several experiments performed in order to study the impact of the strategy chosen for the recognition of proper nouns.  ...  Acknowledgments This research has been partially supported by Plan Nacional de Investigación Científica, Desarrollo e Innovación Tecnológica (TIC2000-0370-C02-01), Ministerio de Ciencia y Tecnología (HP2001-0044) and  ... 
doi:10.1109/dexa.2002.1045906 dblp:conf/dexaw/BarcalaFAGF02 fatcat:6nupqthqy5eodoepvc2ddfrtaa

Report of MIRACLE team for the Ad-Hoc Track in CLEF 2007

José Miguel Goñi-Menoyo, José Carlos González Cristóbal, Julio Villena-Román, Sara Lana-Serrano
2007 Conference and Labs of the Evaluation Forum  
This paper presents the 2007 MIRACLE's team approach to the AdHoc Information Retrieval track.  ...  There is still some room for improvement around multilingual named entities recognition.  ...  Acknowledgements This work has been partially supported by the Spanish R+D National Plan, by means of the project RIMMEL (Multilingual and Multimedia Information Retrieval, and its Evaluation), TIN2004  ... 
dblp:conf/clef/Goni-MenoyoCVL07 fatcat:2tl2h5ipmbemvnsbulnxya5grm

Location Identification Using Stanford NLP

S. Vishnu Manoj
2020 International Journal of Innovative Research in Applied Sciences and Engineering  
The paper also focused on presenting the restricted domain ontology models and concept level vector space model of information retrieval.  ...  Thus forming a significant technique for the question-answering system. This paper inculcates introduction ontology and the definition of a domain ontology for agriculture cultivation.  ...  We have deep gratitude towards our faculties for giving us technical and moral support from time to time  ... 
doi:10.29027/ijirase.v4.i2.2020.617-621 fatcat:u2bo5da3xjgxnpl4iyoqw6m4ui

Phrase recognition and expansion for short, precision-biased queries based on a query log

Erika F. de Lima, Jan O. Pedersen
1999 Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '99  
In this paper we examine the question of query parsing for World Wide Web queries and present a novel method for phrase recognition and expansion.  ...  The optimal syntactic parse for a user query thus obtained is employed for phrase recognition and expansion.  ...  We would specially like to thank Glenn Carroll for sharing his experience in training stochastic CFGs and for his assistance.  ... 
doi:10.1145/312624.312669 dblp:conf/sigir/LimaP99 fatcat:e6t6vrspeneord7xcm7luoicvq

Detecting candidate named entities in search queries

Areej Alasiry, Mark Levene, Alexandra Poulovassilis
2012 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '12  
The information extraction task of Named Entities Recognition (NER) has been recently applied to search engine queries, in order to better understand their semantics.  ...  detecting candidate NEs using grammar annotation and query segmentation with the aid of top-n snippets from search engine results and a web n-gram model, to accurately identify NE boundaries.  ...  'of' followed and preceded by proper nouns such as 'University of Wisconsin' (approximately 2%), and (3) A sequence of proper nouns that include numbers, such as 'Microsoft Office Professional 2003' (approximately  ... 
doi:10.1145/2348283.2348463 dblp:conf/sigir/AlasiryLP12 fatcat:douoe2lesvgvripxtijlcaelj4

FrEX: Extracting Property Expropriation Frame Entities from Real Cases

Roberto Salvaneschi, Daniela Muradore, Andrea Stanchi, Viviana Mascardi
2019 International Conference of the Italian Association for Artificial Intelligence  
for expropriation cases, when retrieving, filtering, and classifying legal documents.  ...  Although FrEX's development is still under way, the results are very encouraging and suggest that it can effectively relieve lawyers and judges from the highly repetitive task of looking for entities relevant  ...  We thank Roberto Bichi, President of the Tribunal of Milan, and Marianna Galioto, President of Civil Section III of the Tribunal of Milan, for sharing,  ... 
dblp:conf/aiia/SalvaneschiMSM19 fatcat:3b4kr7sys5f4hl3hxkffwgpj2y

ISM@FIRE-2014

Dinesh Kumar Prabhakar, Shantanu Dubey, Bharti Goel, Sukomal Pal
2015 Proceedings of the Forum for Information Retrieval Evaluation on - FIRE '14  
Named Entity Recognition is a subtask of information extraction that seeks to locate and classify the proper names in a text.  ...  A Conditional Random Field (CRF) based Stanford Classifier has been used for classification. Tokens are classified hierarchically.  ...  These tokens can be noun phrases, adjectives, prepositions, verbs, articles etc. From these tokens, system identifies proper-noun.  ... 
doi:10.1145/2824864.2824881 dblp:conf/fire/PrabhakarDGP14 fatcat:b6wubklrmnf63ecmskuvpmmcqe

Question Analysis for Arabic Question Answering Systems

Waheeb Ahmed, Babu Anto P
2016 International Journal on Natural Language Computing  
Our Question analysis uses several techniques to analyze any question given in natural language: a Stanford POS Tagger & parser for Arabic language, a named entity recognizer, tokenizer,Stop-word removal  ...  The first step of processing a question in Question Answering(QA) Systems is to carry out a detailed analysis of the question for the purpose of determining what it is asking for and how to perfectly approach  ...  The rule-based chunking for nouns and noun phrases is based on the POS Tagging information produced by Stanford POS Tagger for Arabic[17].  ... 
doi:10.5121/ijnlc.2016.5603 fatcat:n7mw7faccfeknnvzdrfncrmvxy

A Method for Proper Noun Extraction in Kurdish

Hossein Hassani, Marc Herbstritt
2017 Symposium on Languages, Applications and Technologies  
Kurdish proper nouns are not capitalized and they also assume other part-of-speech roles, which leads to a broad ambiguity that should be addressed in Kurdish proper noun recognition applications.  ...  This paper suggests a method for proper noun identification in Kurdish texts.  ...  Dzejla Medjedovic an Assistant Professor and Vice Dean of Graduate Program at the University Sarajevo School of Science and Technology (SSST) for reviewing this paper and providing influential recommendations  ... 
doi:10.4230/oasics.slate.2017.19 dblp:conf/slate/Hassani17 fatcat:dthgc5vy4ve3racqilaavdlc34

QARAB

Bassam Hammo, Hani Abu-Salem, Steven Lytinen
2002 Proceedings of the ACL-02 workshop on Computational approaches to semitic languages -  
To achieve this goal, we use an existing tagger to identify proper names and other crucial lexical items and build lexical entries for them on the fly.  ...  During the last few years the information retrieval community has attacked this problem for English using standard IR techniques with only mediocre success.  ...  The recognition process occurs in multiple stages in which a list of patterns and heuristics may be applied to mark the proper noun.  ... 
doi:10.3115/1118637.1118644 dblp:conf/acl-semitic/HammoALE02 fatcat:75oieazukbbppahtnrlmzqzeam

Named Entity Recognition using Gazetteer Method and N-gram Technique for an Inflectional Language: A Hybrid Approach

Arindam Dey, Bipul Syam Prukayastha
2013 International Journal of Computer Applications  
Named Entity Recognition (NER) is a task to discover the Named Entities (NEs) in a document and then categorize these NEs into diverse Named Entity classes such as Name of Person, Location, River, Organization  ...  In this paper different technique of NER and a brief introduction of Gazetteer method and Hidden Markov Model especially ngram technique has been described.  ...  INTRODUCTION Named Entity Recognition (NER) is an important tool in almost all of the Natural Language processing applications such as Information Retrieval (IR), Information Extraction (IE), Question  ... 
doi:10.5120/14607-2859 fatcat:yf5lef72afaufhyqwvnx4zcjve

Developing classification-based named entity recognizers (NER) for Sambalpuri and Odia applying support vector machines (SVM)

Pitambar Behera, Sharmin Muzaffar
2018 Nepalese Linguistics  
This paper demonstrates the development of named Entity Recognizers (NER) applying Support Vector Machines (SVM) for Sambalpuri and Odia.  ...  The Sambalpuri corpus amounts to 112k word tokens out of which 5,887 are named entities. On the contrary, 250k ILCI corpus has been applied for Odia out of which 18,447 tokens are named entities.  ...  Acknowledgements We are indebted to the reviewers and participants of the 38 th Linguistics Society of Nepal Annual Conference held in 2017 for their suggestions for qualitative improvement.  ... 
doi:10.3126/nl.v33i1.41066 fatcat:domjsbw7wbdkjc5ht44kqchpdi

Location Named-Entity Recognition using Rule-Based Approach for Balinese Texts

Ni Putu Ayu Sherly Anggita S, Ngurah Agus Sanjaya ER
2021 Jurnal Elektronik Ilmu Komputer Udayana  
The system aims to identify proper names in the corpus and classify them into locations class. Precision, recall, and F-measure used for the evaluation.  ...  In Natural Language Processing (NLP), Named Recognition Entity (NER) is a sub-discussion widely used for research.  ...  For example, detecting the entity type for a document written in English can quickly be done by detecting proper nouns. Proper nouns usually start with a capital letter.  ... 
doi:10.24843/jlk.2021.v09.i03.p15 fatcat:2nlabz6ntvdoboegx7re5dcv5y

Software-specific part-of-speech tagging

Deheng Ye, Zhenchang Xing, Jing Li, Nachiket Kapre
2016 Proceedings of the 31st Annual ACM Symposium on Applied Computing - SAC '16  
We define a POS tagset that is suitable for describing software engineering knowledge, select corpus, develop a custom tokenizer, annotate data, design features for supervised model training, and demonstrate  ...  informal languages.  ...  We release our annotated corpus and trained machine learning models (available at https://drive.google.com/open? id=0ByoLWPpAxGVFX3JrWFFDSXBSNDQ) to the soft-  ... 
doi:10.1145/2851613.2851772 dblp:conf/sac/YeXLK16 fatcat:ywpmejvk6jbyxjyrdjfznamj7m

Conceptual Framework for Abstractive Text Summarization

Nikita Munot, Sharvari S. Govilkar
2015 International Journal on Natural Language Computing  
While more and more textual information is available online, effective retrieval is difficult without proper indexing and summarization of the content.  ...  As the volume of information available on the Internet increases, there is a growing need for tools helping users to find, filter and manage these resources.  ...  Then it generates tokens, Name Entity Recognition (NER) and part-of-speech (POS) tags for all the sentences.  ... 
doi:10.5121/ijnlc.2015.4104 fatcat:jf7eiws7ajbmrfzgvtbuyebcqe
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