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Semalt presenta las mejores técnicas y enfoques para extraer contenido de páginas web

Hoy en día, la web se ha convertido en la fuente de datos más extendida en la industria del marketing. Los propietarios de sitios web de comercio electrónico y los vendedores en línea dependen de datos estructurados para tomar decisiones comerciales fiables y sostenibles. Aquí es donde entra en juego la extracción de contenido de la página web. Para obtener datos de la web, necesita enfoques y técnicas integrales que interactúen fácilmente con su fuente de datos.

Actualmente, la mayoría de las técnicas de raspado web se componen de características preempaquetadas que permiten a los raspadores web utilizar enfoques de agrupamiento y clasificación para raspar páginas web. Por ejemplo, para obtener datos útiles de páginas web HTML, deberá preprocesar los datos extraídos y convertir los datos obtenidos en los formatos legibles.

Problemas que surgen al extraer un contenido central de una página web

La mayoría de los sistemas de raspado web usan envoltorios para extraer datos útiles de las páginas web. Los empaquetadores trabajan envolviendo la fuente de información usando sistemas integrados y accediendo a la fuente objetivo sin cambiar el mecanismo central. Sin embargo, estas herramientas se usan comúnmente para una sola fuente.

Para raspar páginas web usando envoltorios, tendrá que incurrir en sus costos de mantenimiento, lo que hace que el proceso de extracción sea bastante costoso. Tenga en cuenta que puede desarrollar un mecanismo de inducción de envoltura si su proyecto de raspado web actual es a gran escala.

Enfoques de extracción de contenido de la página web para considerar

  •  CoreEx 

CoreEx es una técnica heurística que utiliza el árbol DOM para extraer artículos de las plataformas de noticias en línea de forma automática. Este enfoque funciona analizando el número total de enlaces y textos en un conjunto de nodos. Con CoreEx, puede usar el analizador HTML de Java para obtener un objeto de documento. Árbol modelo (DOM), que indica el número de enlaces y textos en un nodo.

  •  Envolvente V 

V-Wrapper es un técnica de extracción de contenido independiente de la plantilla de calidad ampliamente utilizada por scrappers web para identificar un artículo principal del artículo de noticias. V-Wrapper utiliza la biblioteca MSHTML para analizar fuente HTML para obtener un árbol visual. Con este enfoque, puede acceder fácilmente a los datos desde cualquier Nodos de Document Object Model.

V-Wrapper utiliza una relación padre-hijo entre dos bloques de destino, que luego define el conjunto de funciones extendidas entre un elemento secundario y un elemento primario. pproach está diseñado para estudiar usuarios en línea e identificar sus comportamientos de exploración mediante el uso de páginas web seleccionadas manualmente. Con V-Wrapper, puede ubicar características visuales como pancartas y publicidades.

Hoy en día, este método es ampliamente utilizado por los raspadores web para identificar las características en una página web al examinar el bloque principal y determinar el cuerpo de noticias y el título. V-Wrapper usa un algoritmo de extracción para extraer contenido de páginas web que implica identificar y etiquetar el bloque de candidatos.

  •  ECON 

Yan Guo diseñó el enfoque ECON con el objetivo principal de recuperar automáticamente el contenido de las páginas web de noticias. Este método utiliza el analizador HTML para convertir completamente las páginas web en un árbol DOM y utiliza las características completas del árbol DOM para obtener datos útiles.

  •  Algoritmo de RTDM 

El mapeo descendente restringido es un algoritmo de edición de árbol basado en el cruce de árboles donde las operaciones de este enfoque están restringidas a el árbol objetivo se va. Tenga en cuenta que RTDM se usa comúnmente en el etiquetado de datos, la clasificación de páginas web basadas en estructuras y la generación de extractores.

Lisa Thompson
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John O'Neil
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