{"id":789,"date":"2026-10-05T18:31:37","date_gmt":"2026-10-05T16:31:37","guid":{"rendered":"https:\/\/pnicoli.me\/?p=789"},"modified":"2026-10-05T18:33:26","modified_gmt":"2026-10-05T16:33:26","slug":"cade","status":"publish","type":"post","link":"https:\/\/pnicoli.me\/?p=789","title":{"rendered":"cade"},"content":{"rendered":"<div class=\"taxonomy-category wp-block-post-terms\"><a href=\"https:\/\/pnicoli.me\/?cat=10\" rel=\"tag\">Programming<\/a><span class=\"wp-block-post-terms__separator\">, <\/span><a href=\"https:\/\/pnicoli.me\/?cat=12\" rel=\"tag\">Python<\/a><\/div>\n\n\n<h1 id=\"compass-aligned-distributional-embeddings\" class=\"wp-block-heading\">Compass-aligned Distributional Embeddings<\/h1>\n\n\n\n<p id=\"gspb_text-id-gsbp-bb302ed\" class=\"gspb_text gspb_text-id-gsbp-bb302ed \">This package contains Python code to generate compass aligned distributional embeddings (CADE). Comparing word vectors in different corpora requires alignment. We propose a method to aligned distributional representation based on word2vec. This method is efficient and it is based on a simple heuristic: we train a general word embedding, the compass and we use this embedding to freeze one of the layers of the CBOW architecture.<br><br>See the AAAI and Arxiv pre-print papers for more details.<\/p>\n\n\n\n<div class=\"wp-block-greenshift-blocks-image gspb_image gspb_image-id-gsbp-e533f88\" id=\"gspb_image-id-gsbp-e533f88\"><img decoding=\"async\" src=\"https:\/\/pnicoli.me\/wp-content\/uploads\/2026\/10\/CADE.png\" data-src=\"\" alt=\"\" loading=\"lazy\" width=\"1793\" height=\"569\"\/><\/div>\n\n\n\n<div class=\"gspb_button_wrapper gspb_button-id-gsbp-749aa5b\" id=\"gspb_button-id-gsbp-749aa5b\"><a class=\"wp-block-greenshift-blocks-buttonbox gspb-buttonbox wp-element-button\" href=\"https:\/\/github.com\/pscrapy\/hiveplot\" target=\"_blank\" rel=\"noopener\"><span class=\"gspb-buttonbox-textwrap\"><span class=\"gspb-buttonbox-icon\"><svg class=\"\" style=\"display:inline-block;vertical-align:middle\" width=\"15\" height=\"15\" viewBox=\"0 0 1024 1024\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path style=\"fill:#565D66\" d=\"M923.8 0c-11.46 0-23.18 2.2-34.78 7.040l-831.54 383.78c-95.94 44.78-63.96 185.5 38.38 185.5h351.82v351.82c0 60.020 48.42 95.86 97.48 95.86 34.6 0 69.5-17.8 88.020-57.48l383.8-831.56c27.14-65.18-28.7-134.96-93.18-134.96zM958.9 108.16l-383.7 831.32c-6.36 13.64-16.48 20.56-30.060 20.56-11.6 0-33.52-6.66-33.52-31.88v-415.8h-415.76c-22.9 0-29.28-17.66-30.98-25.26-2.2-9.86-2.54-27.96 19.4-38.2l829.36-382.82c3.42-1.42 6.74-2.1 10.18-2.1 10.84 0 22.98 7.3 30.22 18.16 4.38 6.58 8.64 16.82 4.86 26.020z\"><\/path><\/svg><\/span><span class=\"gspb-buttonbox-text\"><span class=\"gspb-buttonbox-title\">Learn more on Github<\/span><\/span><\/span><\/a><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Compass-aligned Distributional Embeddings<\/p>\n","protected":false},"author":1,"featured_media":792,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_seopress_titles_title":"","_seopress_titles_desc":"","_seopress_robots_index":"yes","_seopress_robots_follow":"","_seopress_robots_imageindex":"","_seopress_robots_snippet":"","_seopress_robots_primary_cat":"","_seopress_robots_breadcrumbs":"","_seopress_robots_freeze_modified_date":"","_seopress_robots_custom_modified_date":"","_seopress_robots_canonical":"","_seopress_social_fb_title":"","_seopress_social_fb_desc":"","_seopress_social_fb_img":"","_seopress_social_fb_img_attachment_id":0,"_seopress_social_fb_img_width":0,"_seopress_social_fb_img_height":0,"_seopress_social_twitter_title":"","_seopress_social_twitter_desc":"","_seopress_social_twitter_img":"","_seopress_social_twitter_img_attachment_id":0,"_seopress_social_twitter_img_width":0,"_seopress_social_twitter_img_height":0,"_seopress_redirections_value":"","_seopress_redirections_enabled":"","_seopress_redirections_enabled_regex":"","_seopress_redirections_logged_status":"","_seopress_redirections_param":"","_seopress_redirections_type":0,"_seopress_analysis_target_kw":"","_gspb_post_css":".gspb_text-id-gsbp-bb302ed{margin-top:0!important}#gspb_image-id-gsbp-e533f88 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