Hot products from TV and Social Media

The xLiMe technology allows to detect products – such as shoes – in TV streams and in Social Media messages.

This information is used to generate recommendations in online shops.

The use of external evidence results in dynamic content that is up-to-date, interesting and inspiring, and follows current trends in real time.


Links

Watch our screencast

About ECONDA


Contact

Philipp Sorg
research(at)econda.de


Efficiently Spotting Social Media Opinions Across Modalities and Languages

Keeping track of a daily volume of up to 100 million relevant social media comments and customer opinions in different media, languages and formats in order to obtain valuable insights for customers requires usually a great amount of manual effort.

Social media contributions have to be read, watched and categorized in order to meet the need of deep and high qualitative understanding of the data associated with many service and market research use cases.

xLiMe technology supports the automatization of this process in VICO Analytics by clustering and structuring data across media and across languages, this way significantly reducing manual effort. This enables us to deliver time more efficently and at the same time well-grounded research services.


Links

Watch our screencast

About VICO Analytics

About xLiMe Demo Station

About VICO www.vico-research.com/blog www.twitter.com/vico_news www.facebook.com/vico.friend


Contact

Philipp Tiedt
philipp.tiedt(at)vico-research.com
Tel. +49(0)7 11. 78 78 29-22
Fax +49(0)7 11. 78 78 29-10
Mobile +49(0)1 77. 8 71 39 41

Find Related TV Shows

In Zattoo’s web application, users can browse TV shows via semantic linkings.

Based on speech-to-text transcriptions of the actual TV shows, xLiMe technology provides “related shows” recommendations that go beyond traditional similarity recommendation approaches which are usually mostly based on curated TV listings data or collaborative filtering approaches.

True understanding of the actual audio-visual content allows for highly relevant recommendations.


Links

Watch our screencast

xLiMe Deliverable D.2: Semantic Disambiguation Prototype

xLiMe Deliverable D.7.2.1: Early Prototype SEARCH

xLiMe Deliverable D.7.2.2: Intermediate Prototype SEARCH

About Zattoo


Contact

Joerg Schindler
joerg.schindler(at)zattoo.com

Brexit Showcase

Two xLiMe demonstrators showing the capabilities of xLiMe technology to interlink media items in different languages and modalities. Search and explore the media items in our 'live' showcase and do the same using a dataset from June 2016 focusing on the EU (Brexit) referendum.


Links

Watch our screencast

Live showcase

Brexit Showcase: coming soon

Brexit Dataset: coming soon

Code for web application: https://github.com/xlime-eu/xlime-showcase


Contact

Ronald Denaux
rdenaux(at)expertsystem.com

xKnowSearch

A novel entity-based system for multilingual and cross-lingual information retrieval

Representing keyword queries and documents in their semantic forms by leveraging the multilingual knowledge base on the Web

Facilitating query disambiguation and expansion and also overcoming the language barrier between queries and documents in different languages


Links

See our demo

Watch our screencast


Publications

Lei Zhang, Achim Rettinger, Ji Zhang. A Knowledge Base Approach to Cross-lingual Keyword Query Interpretation. The 15th International Semantic Web Conference (ISWC'16), Springer, October, 2016

Lei Zhang, Michael Färber, Achim Rettinger. XKnowSearch! Exploiting Knowledge Bases for Entity-based Cross-lingual Information Retrieval. The 25th ACM International on Conference on Information and Knowledge Management (CIKM'16), ACM, October, 2016


Contact

Lei Zhang
1.zhang(at)kit.edu
http://www.aifb.kit.edu/web/Lei_Zhang/en

Semantic Image and Video Annotation

Semantic image and video annotation tools aim to automatically extract high level information from visual content.

The xLiMe semantic visual annotator can be applied to detect and localize within an image a specific object of interest or a brand logo, thus enriching image and/or video metadata.

The xLiMe semantic visual annotator allows you to follow your favourite brand or to monitor a topic of interest both on social network or TV mainstream.


Links

Watch our screencast

xLiMe Deliverable D.3.2.2: Final Prototype for Video Annotation


Contact

Gloria Zen
gloria.zen(at)unitn.it
UniTN

Dubravko Culibrk
info(at)panonit.com
Panonit

Entity Summarization

LinkSUM? Awesome!

Links



Contact

Andreas Thalhammer (KIT)
ELES (pronounced "Alice") is a lightweight combination of entity linking and entity summarization. In the demo, we use an entity linking service to analyze text and link fragments to entities of the DBpedia knowledge base. The LinkSUM summarizer (interfaced via the SUMMA API definition) produces fact-based summaries of DBpedia entities. The two applications are combined on the client side through the "Internationalization Tag Set 2.0" W3C recommendation and lightweight jQuery-based interfaces.

Cross-channel and Cross-media Recommender

xLiMe semantic integrator leverages implicit or latent semantics in the textual data present in different languages to provide search, cross-channel recommendations and analytic's.


Links

Code

Watch our screencast


Contact

Aditya Mogadala
AIFB
KIT

Cross-media data correlation

In Event Registry users can identify correlations between different data types, such as mentions of an entity in the media or its popularity on social media, stock prices of companies, number of sold items, etc.

Event Registry is a media monitoring platform that collects news published globally. One of the features it provides is also tracking of how frequently a particular entity is mentioned in the media. This allows one to obtain a time-series data of mentions over several years. Along with mentions of entities, Event Registry also stores time-series information about other data types, such as stock prices of companies, trading volumes, exchange rates, etc. With several millions of time-series, Event Registry can then identify for a given time-series what are other time-series that correlate the most with it. This can be used to identify simple relations between various data types as well as potential causation.


Links

Running demo

Watch our screencast

xLime Deliverable D5.3.1: Early analytics prototype

xLime Deliverable D5.3.2: Final analytics prototype


Contact

Gregor Leban
gregor.leban@ijs.si
JSI

Frontend components

Build applications on top of the xLiMe platform by using REST services and a library of web components.


Links

Watch our screencast

Code for REST Services: https://github.com/xlime-eu/xlime-frontend-services

Code for web components: https://github.com/xlime-eu/xlime-polymer-elements

Demo of web components: http://xlime-eu.github.io/xlime-polymer-elements

Public REST endpoint: http://expertsystemlab.com/frontend-services

Code for web application: https://github.com/xlime-eu/xlime-showcase


Contact

Ronald Denaux
rdenaux(at)expertsystem.com

Find out more!


         

or contact Dr. Achim Rettinger (Coordinator)