{"id":51141715,"url":"https://github.com/argrecsys/arg-ir-tool","last_synced_at":"2026-07-14T07:00:56.024Z","repository":{"id":40381875,"uuid":"452060498","full_name":"argrecsys/arg-ir-tool","owner":"argrecsys","description":"ArgIR: Tool for annotation and retrieval of argumentative information from textual content. A case study in the Decide Madrid database. 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A case study in the \u003ca href=\"https://decide.madrid.es\" target=\"_blank\"\u003eDecide Madrid\u003c/a\u003e database.\n\nWe present a tool that not only allows to retrieve argumentative information, but also to annotate new arguments and/or validate them (in terms of their *topical relevance* and *rhetorical quality*). The search runs on \u003ca href=\"https://lucene.apache.org/\" target=\"_blank\"\u003eApache Lucene\u003c/a\u003e and the results (proposals and comments) are re-ranked according to their level of controversy or the number and quality of arguments they have.\n\nThis project takes advantage of the arguments previously extracted (from the citizen proposals of the Decide Madrid platform) in the \u003ca  href=\"https://github.com/argrecsys/arg-miner\" target=\"_blank\"\u003eargrecsys/arg-miner\u003c/a\u003e repository.\n\n## Papers\nThis work (v1.0) was presented as a long paper at \u003ca href=\"https://www.irit.fr/CIRCLE/\"\u003eCIRCLE (Joint Conference of the Information Retrieval Communities in Europe) 2022\u003c/a\u003e. CIRCLE 2022 was hosted by the Université de Toulouse, France, 4-7th July 2022. The paper can be found \u003ca href=\"https://github.com/argrecsys/arg-ir-tool/tree/main/papers/\"\u003ehere\u003c/a\u003e.\n\n## Screenshots\n**Argument-enhanced Information Retrieval** tool: allows the retrieval of argumentative information from textual content.\n\n![arg-ir-gui-main](https://raw.githubusercontent.com/argrecsys/arg-enhanced-ir/main/images/gui-main.gif)\n\n**Arguments Annotation** form: allows manual annotation and validation of arguments.\n\n![arg-ir-gui-annotation](https://raw.githubusercontent.com/argrecsys/arg-enhanced-ir/main/images/gui-annotation.gif)\n\n## Annotation and validation\nThe tool allows you to annotate/edit arguments, as well as validate their relevance and quality.\nBelow is an example of the generated \u003ca href=\"https://github.com/argrecsys/arg-enhanced-ir/blob/main/data/results/labels.csv\" target=\"_blank\"\u003evalidation file\u003c/a\u003e.\n\n| proposal_id | argument_id | relevance | quality | timestamp | username |\n| ----------- | ----------- | --------- | ------- | --------- | -------- |\n| 7 | 7-85675-1-1 | VERY_RELEVANT | SUFFICIENT | 10/3/2022 20:53:00 | andres.segura |\n| 1419 | 1419-30381-1-1 | RELEVANT | SUFFICIENT | 17/02/2022 23:04 | andres.segura |\n| 2576 | 2576-0-1-1 | VERY_RELEVANT | HIGH_QUALITY | 16/02/2022 17:31 | andres.segura |\n| 10996 | 10996-0-1-1 | VERY_RELEVANT | HIGH_QUALITY | 24/02/2022 20:12 | andres.segura |\n| 26787 | 26787-204339-1-1 | NOT_RELEVANT | LOW_QUALITY | 2022-03-09 16:39:43 | andres.segura |\n\n## Validation\nAs a preliminary offline evaluation, using the developed tool, we manually validated 20% of the arguments extracted by the simple syntactic pattern-based method. For the \u003cem\u003etopical relevance\u003c/em\u003e metric, 8.6% of the arguments were labeled as \u003cem\u003espam\u003c/em\u003e, 36.9% as \u003cem\u003enot relevant\u003c/em\u003e, 39.9% as \u003cem\u003erelevant\u003c/em\u003e, and 14.6% as \u003cem\u003every relevant\u003c/em\u003e, whereas for the \u003cem\u003erhetoric quality\u003c/em\u003e metric, 42.3% of the arguments were of \u003cem\u003elow quality\u003c/em\u003e, 40.6% of \u003cem\u003esufficient quality\u003c/em\u003e, and 17.1% of \u003cem\u003ehigh quality\u003c/em\u003e. Although these results are modest, they can be considered acceptable as baseline values, taking into account they were obtained with a heuristic method that does not require training data and parameter tuning.\n\n## Dependencies\nThe implemented solutions depend on or make use of the following libraries and .jar files:\n- JDK 16\n- \u003ca href=\"https://lucene.apache.org/\" target=\"_blank\"\u003eApache Lucene\u003c/a\u003e 9.0\n- MySQL Connector 8.0.22\n- \u003ca href=\"https://mongodb.github.io/mongo-java-driver/\" target=\"_blank\"\u003eMongoDB Java Driver\u003c/a\u003e 3.12.10\n- Snake YAML 1.9\n- JSON Java 20210307\n- OpenCSV 4.1\n\n## Execution and Use\nThe project has an executable package in the `\\jar` folder, called `ArgumentIR.jar`. To run the tool from the Command Prompt (CMD), execute the following commands:\n\n``` shell\n  cd \"arg-ir-tool\\jar\\\"\n  java -jar ArgumentIR.jar\n```\n\n# Documentation\nPlease read the [contributing](https://github.com/argrecsys/arg-ir-tool/blob/main/docs/CONTRIBUTING.md) and [code of conduct](https://github.com/argrecsys/arg-ir-tool/blob/main/docs/CODE_OF_CONDUCT.md) documentation.\n\n## Authors\nCreated on Jan 25, 2022  \nCreated by:\n- \u003ca href=\"https://github.com/ansegura7\" target=\"_blank\"\u003eAndrés Segura-Tinoco\u003c/a\u003e\n- \u003ca href=\"http://arantxa.ii.uam.es/~cantador/\" target=\"_blank\"\u003eIv\u0026aacute;n Cantador\u003c/a\u003e\n\n## License\nThis project is licensed under the terms of the \u003ca href=\"https://github.com/argrecsys/arg-enhanced-ir/blob/main/LICENSE\"\u003eApache License 2.0\u003c/a\u003e.\n\n## Acknowledgements\nThis work was supported by the Spanish Ministry of Science and Innovation (PID2019-108965GB-I00).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fargrecsys%2Farg-ir-tool","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fargrecsys%2Farg-ir-tool","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fargrecsys%2Farg-ir-tool/lists"}