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{
    "pk": 25932,
    "title": "Use of Lexical Statistics for CompoundWord Recognition and Segmentation in\nTurkish",
    "subtitle": null,
    "abstract": "Compound words are cross-linguistic morphological phenomena that occur in all languages. Compound words are\nwidely accepted to be stored in the lexicon but their constituents need to be accessed during both language learning and production\nprocesses. In this study, the use of corpora was investigated for how to differentiate single-stem words from single-word\ncompounds and then how to segment compound words when no phonological information is available. Stems and morphs discovered\nin manual segmentations of the METU-Sabancı Turkish Treebank and the CHILDES were employed in the compound\nword recognition task and the results were compared. The METU Turkish Corpus (with about 2 million words) and a webcorpus\n(with about 490 million of Turkish words) were utilized in the segmentation task. The results emphasize that the lexicon\ncan be morpheme-based; and lexical frequencies are effective heuristics in compound word recognition and segmentation",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Member Abstracts",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/9kk766jd",
    "frozenauthors": [
        {
            "first_name": "Ozkan",
            "middle_name": "",
            "last_name": "Kilie",
            "name_suffix": "",
            "institution": "Graduate Student",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2015-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/25932/galley/15556/download/"
        }
    ]
}