Information retrieval and structural complexity of legal trees
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2022
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866916394900127744 |
|---|---|
| author | Förster, Yanik-Pascal Annibale, Alessia Gamberi, Luca Tzanis, Evan Vivo, Pierpaolo |
| author_facet | Förster, Yanik-Pascal Annibale, Alessia Gamberi, Luca Tzanis, Evan Vivo, Pierpaolo |
| contents | We introduce a model for the retrieval of information hidden in legal texts. These are typically organised in a hierarchical (tree) structure, which a reader interested in a given provision needs to explore down to the "deepest" level (articles, clauses,...). We assess the structural complexity of legal trees by computing the mean first-passage time a random reader takes to retrieve information planted in the leaves. The reader is assumed to skim through the content of a legal text based on their interests/keywords, and be drawn towards the sought information based on keywords affinity, i.e. how well the Chapters/Section headers of the hierarchy seem to match the informational content of the leaves. Using randomly generated keyword patterns, we investigate the effect of two main features of the text -- the horizontal and vertical coherence -- on the searching time, and consider ways to validate our results using real legal texts. We obtain numerical and analytical results, the latter based on a mean-field approximation on the level of patterns, which lead to an explicit expression for the complexity of legal trees as a function of the structural parameters of the model. Policy implications of our results are briefly discussed. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2203_02259 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Information retrieval and structural complexity of legal trees Förster, Yanik-Pascal Annibale, Alessia Gamberi, Luca Tzanis, Evan Vivo, Pierpaolo Physics and Society Statistical Mechanics We introduce a model for the retrieval of information hidden in legal texts. These are typically organised in a hierarchical (tree) structure, which a reader interested in a given provision needs to explore down to the "deepest" level (articles, clauses,...). We assess the structural complexity of legal trees by computing the mean first-passage time a random reader takes to retrieve information planted in the leaves. The reader is assumed to skim through the content of a legal text based on their interests/keywords, and be drawn towards the sought information based on keywords affinity, i.e. how well the Chapters/Section headers of the hierarchy seem to match the informational content of the leaves. Using randomly generated keyword patterns, we investigate the effect of two main features of the text -- the horizontal and vertical coherence -- on the searching time, and consider ways to validate our results using real legal texts. We obtain numerical and analytical results, the latter based on a mean-field approximation on the level of patterns, which lead to an explicit expression for the complexity of legal trees as a function of the structural parameters of the model. Policy implications of our results are briefly discussed. |
| title | Information retrieval and structural complexity of legal trees |
| topic | Physics and Society Statistical Mechanics |
| url | https://arxiv.org/abs/2203.02259 |