Indexes: Term Vectors

Term Vector is a representation of a text document as a vector of identifiers that can be used for similarity searches, information filtering, information retrieval, and indexing. In RavenDB the feature like MoreLikeThis is leveraging the term vectors to accomplish its purposes.

To create an index and enable Term Vectors on a specific field we can create an index using the AbstractIndexCreationTask, then specify the term vectors there, or define our term vectors in the IndexDefinition (directly or using the IndexDefinitionBuilder).

class BlogPosts_ByTagsAndContent extends AbstractIndexCreationTask {
    constructor() {
        super();

        this.map = `docs.Posts.Select(post => new {     
            tags = post.tags,     
            content = post.content 
        })`; 

        this.index("content", "Search");
        this.termVector("content", "WithPositionsAndOffsets");
    }
}

const builder = new IndexDefinitionBuilder("BlogPosts/ByTagsAndContent");
builder.map = `docs.Posts.Select(post => new {     
    tags = post.tags,     
    content = post.content 
})`; 

builder.indexesStrings["content"] = "Search";
builder.termVectorsStrings["content"] = "WithPositionsAndOffsets";

const indexDefinition = builder.toIndexDefinition(store.conventions);

await store.maintenance.send(new PutIndexesOperation(indexDefinition));

The available Term Vector options are: