Tootfinder

Police recover items at NYC shooter's apartment https://www.espn.com/nfl/story/_/id/45882079/police-recover-items-nyc-shooter-las-vegas-apartment

This is pretty awesome, well done #Pembrokeshire CC!
Small electrical items now accepted in kerbside #recycling collections
https://newsroom.pembrokeshire.gov.uk/news/small-electrical-items-now-accepted-in-kerbside-recycling-collections

Talking Transactions: Decentralized Communication through Ethereum Input Data Messages (IDMs)
Xihan Xiong, Zhipeng Wang, Qin Wang, Endong Liu, Pascal Berrang, William Knottenbelt
https://arxiv.org/abs/2505.24724

Talking Transactions: Decentralized Communication through Ethereum Input Data Messages (IDMs)
Can you imagine, blockchain transactions can talk! In this paper, we study how they talk and what they talk about. We focus on the input data field of Ethereum transactions, which is designed to allow external callers to interact with smart contracts. In practice, this field also enables users to embed natural language messages into transactions. Users can leverage these Input Data Messages (IDMs) for peer-to-peer communication. This means that, beyond Ethereum's well-known role as a financial …

Interact2Vec -- An efficient neural network-based model for simultaneously learning users and items embeddings in recommender systems
Pedro R. Pires, Tiago A. Almeida
https://arxiv.org/abs/2506.22648

Interact2Vec -- An efficient neural network-based model for simultaneously learning users and items embeddings in recommender systems
Over the past decade, recommender systems have experienced a surge in popularity. Despite notable progress, they grapple with challenging issues, such as high data dimensionality and sparseness. Representing users and items as low-dimensional embeddings learned via neural networks has become a leading solution. However, while recent studies show promising results, many approaches rely on complex architectures or require content data, which may not always be available. This paper presents Intera…

amazon_copurchases: Amazon co-purchasing network (2003)
Network of items for sale on amazon.com in 2003 and the items they "recommend" (via the "Customers Who Bought This Item Also Bought" feature). If one item is frequently co-purchased with another, then the first item recommends the second.
This network has 410236 nodes and 3356824 edges.
Tags: Economic, Commerce, Unweighted

‘Britain’s most tattooed man’ claims he is unable to watch p*rn as ‘new age check system mistakes his ink for a mask’
https://needtoknow.co.uk/2025/07/30/britains-most-tattooed-man-claims-he-i…

‘Britain’s most tattooed man’ claims he is unable to watch p*rn as 'new age check system mistakes his ink for a mask' | Need To Know
Britain’s most tattooed man says new UK age checks block him from p*rn sites as facial recognition mistakes his tattoos for a mask, calling the tech discriminatory.

Exploring AR Label Placements in Visually Cluttered Scenarios
Ji Hwan Park, Braden Roper, Amirhossein Arezoumand, Tien Tran
https://arxiv.org/abs/2507.00198

Exploring AR Label Placements in Visually Cluttered Scenarios
We investigate methods for placing labels in AR environments that have visually cluttered scenes. As the number of items increases in a scene within the user' FOV, it is challenging to effectively place labels based on existing label placement guidelines. To address this issue, we implemented three label placement techniques for in-view objects for AR applications. We specifically target a scenario, where various items of different types are scattered within the user's field of view, and multip…

Excellent keynote in the #SemDH2025 workshop by Laura Hollink on Cultural Bias in Linked Open Data. Laura is addressing all bias related aspects in cultural heritage items itself, in the data representing it, the data schemata, vocabularies, and ontologies on which the data are based, as well as in the knowledge representation languages used to create the schemata.

Had so much fun today at the V&A East Storehouse in London - a spectacular #museum and public display of their stored items.
Marvellous exhibits inside great #architecture
#exhibition

Not Just What, But When: Integrating Irregular Intervals to LLM for Sequential Recommendation
Wei-Wei Du, Takuma Udagawa, Kei Tateno
https://arxiv.org/abs/2507.23209 https://

Not Just What, But When: Integrating Irregular Intervals to LLM for Sequential Recommendation
Time intervals between purchasing items are a crucial factor in sequential recommendation tasks, whereas existing approaches focus on item sequences and often overlook by assuming the intervals between items are static. However, dynamic intervals serve as a dimension that describes user profiling on not only the history within a user but also different users with the same item history. In this work, we propose IntervalLLM, a novel framework that integrates interval information into LLM and inco…