{"id":15520815,"url":"https://github.com/proycon/phd-thesis","last_synced_at":"2026-01-18T19:01:26.692Z","repository":{"id":66967670,"uuid":"119515846","full_name":"proycon/phd-thesis","owner":"proycon","description":"PhD dissertation: Context as Linguistic Bridges","archived":false,"fork":false,"pushed_at":"2020-05-22T19:13:02.000Z","size":70461,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-04-04T11:07:16.641Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"TeX","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/proycon.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2018-01-30T09:47:29.000Z","updated_at":"2020-05-22T19:19:14.000Z","dependencies_parsed_at":"2023-03-01T16:15:36.370Z","dependency_job_id":null,"html_url":"https://github.com/proycon/phd-thesis","commit_stats":null,"previous_names":[],"tags_count":5,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/proycon%2Fphd-thesis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/proycon%2Fphd-thesis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/proycon%2Fphd-thesis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/proycon%2Fphd-thesis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/proycon","download_url":"https://codeload.github.com/proycon/phd-thesis/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247289133,"owners_count":20914456,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-10-02T10:29:27.364Z","updated_at":"2026-01-18T19:01:26.684Z","avatar_url":"https://github.com/proycon.png","language":"TeX","funding_links":[],"categories":[],"sub_categories":[],"readme":"The actual thesis can be found here: https://github.com/proycon/phd-thesis/blob/master/thesis/thesis.pdf\n\nShort Summary\n-------------\n\n*Context as Linguistic Bridges* is a study that focusses on the role of context information in machine translation, i.e.\nautomated translation by computers.  The underlying intuition is that the context in which a word or phrase appears is\nan important cue for the translation of that word or phrase. Consider, for example, the two different meanings of the word\n*\"bank\"* in the sentences *\"I put my money on the bank\"* and *\"The ship got stuck on the bank\"*.\n\nWe developed classifier-based solutions that work well in Word Sense Disambiguation tasks like the above example, and\nintegrate these in a statistical machine translation system.  Our main question is to find to what extent can we improve\nautomated translation by explicitly modelling such context information.\n\nWe find, however, no significant improvement over already existing models, and we infer that the information we model\nand add explicitly must already be implicitly and sufficiently available to the existing models.\n\nKorte samenvatting\n-------------------\n\n*Context as Linguistic Bridges* is een studie die zich richt op de rol van contextinformatie bij het\nautomatisch vertalen door computers. Het achterliggende idee is dat de context waarin een woord of\nzinsnede voorkomt een belangrijke informatie levert om tot een vertaling te kunnen komen. Neem bijvoorbeeld de twee\nbetekenissen van het woord \"bank\" in de zinnen \"Ik zet mijn geld op de bank\" en \"De hond mag niet op de bank\".\n\nWe hebben classificatiesystemen ontwikkeld die goed werken in disambiguatietaken zoals in het voorbeeld hierboven, en\nintegreren deze in een statistisch automatisch vertaalsysteem. Onze hoofdvraag is te onderzoeken in hoeverre we de\nvertaalkwaliteit kunnen verbeteren door deze informatie expliciet te modelleren.\n\nOnze bevindingen, echter, tonen aan dat er geen significante verbetering te behalen valt ten opzichte van de al bestaande\nmodellen en leiden hieruit af dat de informatie die we expliciet proberen toe te voegen, al impliciet en in voldoende\nmate aanwezig is in de bestaande modellen.\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fproycon%2Fphd-thesis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fproycon%2Fphd-thesis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fproycon%2Fphd-thesis/lists"}