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1	Patterns: An Increase in
	German Nominalization; Stefan Hartmann
	In: http://www.uk-cla.org.uk/files/proceedings/Hartmann.pdf (2014)
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2	Spelling of Derivationally Complex Words: The Role of Phonological, Orthographic, and Morphological Features
	Sofia Benson-goldberg
	In: http://scholarcommons.usf.edu/cgi/viewcontent.cgi?article%3D6378%26context%3Detd (2014)
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3	Quantifying the value of pronunciation lexicons for keyword search in low resource languages
	Guoguo Chen; Sanjeev Khudanpur; Daniel Povey...
	In: http://www.clsp.jhu.edu/%7Eguoguo/papers/icassp2013_lexicon_value.pdf (2013)
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4	1 Quantifier Words And Their Multi-functional(?) Parts*
	Anna Szabolcsi; James Doh Whang; Vera Zu
	In: http://semanticsarchive.net/Archive/GIxYWYyY/szabolcsi_whang_zu_quantifier_words_march_2013.pdf (2013)
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5	Reconstructing the *s- prefix in Old Chinese
	In: http://hal.inria.fr/docs/00/78/11/53/PDF/MeiResponseTNR_Doulos_LS_final_Nov_14_2011.pdf (2013)
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6	The romanian neuter examined through a two-gender n-gram classification system
	Liviu P. Dinu; Vlad Niculae
	In: http://www.lrec-conf.org/proceedings/lrec2012/pdf/651_Paper.pdf (2012)
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7	A finite-state morphological transducer for Kyrgyz
	Jonathan North Washington; Mirlan Ipasov; Francis M. Tyers...
	In: http://www.lrec-conf.org/proceedings/lrec2012/pdf/1077_Paper.pdf (2012)
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8	Reviewed by:
	Juhani Järvikivi; Pirita Pyykkönen; Harald Baayen...
	In: ftp://ftp.ncbi.nlm.nih.gov/pub/pmc/f2/9a/Front_Psychol_2011_Oct_25_2_282.tar.gz (2011)
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9	Non-Canonical Inflection: Data, Formalisation and Complexity Measures
	Benoît Sagot; Géraldine Walther
	In: http://hal.inria.fr/docs/00/61/53/06/PDF/sfcm11.pdf (2011)
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10	Using Kohonen Maps of Chinese Morphological Families to Visualize the Interplay of Morphology and Semantics in Chinese
	Bruno Galmar
	In: http://wing.comp.nus.edu.sg/~antho/O/O11/O11-2005.pdf (2010)
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11	Developing Punjabi Morphology, Corpus and Lexicon. The 24th Pacific Asia conference on Language, Information and Computation
	Muhammad Humayoun; Aarne Ranta
	In: http://www.lama.univ-savoie.fr/~humayoun/punjabi/downloads/Punjabi-paper-paclic24.pdf (2010)
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12	A cross-linguistic model of the acquisition of inflectional morphology
	Themis Karaminis; Michael S. C. Thomas
	In: http://www.psyc.bbk.ac.uk/research/DNL/personalpages/cogsci2010-Karaminis-Thomas-MIG.pdf (2010)
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13	Effective Unsupervised Arabic Word Stemming: Towards an Unsupervised Radicals Extraction IAJIT First Online Publication
	Ahmed Khorsi. - 2010
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14	Morphological Alternations at the Intonational Phrase Edge The Case of K’ichee’
	Robert Henderson
	In: http://digitalcommons.wayne.edu/cgi/viewcontent.cgi?article%3D1025%26context%3Denglishfrp (2009)
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15	General
	Studia Linguistica Upsaliensia; Edited Anju Saxena; Åke Viberg...
	In: http://uu.diva-portal.org/smash/get/diva2%3A275878/FULLTEXT03.pdf (2009)
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16	A corpus-based survey of four electronic Swahili–English bilingual dictionaries
	Guy De Pauw
	In: http://www.ajol.info/index.php/lex/article/viewFile/49134/35479/ (2009)
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17	MorphoNet: Exploring the Use of Community Structure for Unsupervised Morpheme Analysis
	Delphine Bernhard
	In: http://clef.isti.cnr.it/2009/working_notes/morpho-papers/bernhard-paperCLEF2009.pdf (2009)
	Abstract: This paper investigates a novel approach to unsupervised morphology induction relying on community detection in networks. In a first step, morphological transformation rules are automatically acquired based on graphical similarities between words. These rules encode substring substitutions for transforming one word form into another. The transformation rules are then applied to the construction of a lexical network. The nodes of the network stand for words while edges represent transformation rules. In the next step, a clustering algorithm is applied to the network to detect families of morphologically related words. Finally, morpheme analyses are produced based on the transformation rules and the word families obtained after clustering. While still in its preliminary development stages, this method obtains encouraging results at Morpho Challenge 2009, which demonstrate the viability of the approach.
	Keyword: Categories and Subject Descriptors I.2 [Artificial Intelligence; Experimentation; I.2.6 Learning; I.2.7 Natural Language Processing General Terms Algorithms; Languages Keywords morphology induction
	URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.515.871 http://clef.isti.cnr.it/2009/working_notes/morpho-papers/bernhard-paperCLEF2009.pdf
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18	Putting semantics into WordNet’s ”morphosemantic” links
	Christiane Fellbaum; Anne Osherson; Peter E. Clark
	In: http://wordnet.princeton.edu/wordnet/publications/poznan.springer.pdf (2009)
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19	O.: Unsupervised Morpheme Discovery with Allomorfessor
	Sami Virpioja; Oskar Kohonen
	In: http://research.ics.aalto.fi/events/morphochallenge2009/papers/virpioja-paperCLEF2009.pdf (2009)
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20	Unsupervised Acquiring of Morphological Paradigms from Tokenized Text
	Daniel Zeman; Univerzita Karlova
	In: http://ufal.mff.cuni.cz/~zeman/publikace/2007-01/mc2007.pdf (2007)
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