KNITTIR: Syntactical text indexing for analytics

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AWWSYK7YA" target="_blank" >RIV/00216208:11320/26:WWSYK7YA - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1145/3677389.3702486" target="_blank" >http://dx.doi.org/10.1145/3677389.3702486</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3677389.3702486" target="_blank" >10.1145/3677389.3702486</a>

Result language

angličtina

Original language name

KNITTIR: Syntactical text indexing for analytics

Original language description

Scalable text analytics requires retrieval of similar text regions spread across millions of documents. It also requires that we can reason about entities by categorizing them; contrasting them to other entities; and ranking them using time and numbers. We present knittir that assists in such complex text analytical tasks. knittir uses semantic annotations such as parts-of-speech, named entities, and their syntactical relationships to words in text. To simplify text analytics, knittir uses a new search framework wherein a vertical partitioning of semantically annotated text is used. This allows users to aggregate and manipulate evidences to their queries from multiple text regions spread across millions of documents. To scale analytical queries, knittir creates indexes using the syntactical modeling of annotated text. Our experiments over 22 million documents show that knittir obtains speedups of up to 60× for performing similarity search and up to 69K× for reasoning tasks. © 2024 Copyright held by the owner/author(s).

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proc. ACM IEEE Joint Conf. Digit. Libr.

ISBN

979-8-4007-1093-3

ISSN

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e-ISSN

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Number of pages

12

Pages from-to

1-12

Publisher name

Institute of Electrical and Electronics Engineers Inc.

Place of publication

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Event location

Hong Kong

Event date

Jan 1, 2026

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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