Deep Group Interest Modeling of Full Lifelong User Behaviors for CTR Prediction

Extracting users' interests from their lifelong behavior sequence is crucial for predicting Click-Through Rate (CTR). Most current methods employ a two-stage process for efficiency: they first select historical behaviors related to the candidate item and then deduce the user's interest from this narrowed-down behavior sub-sequence. This two-stage paradigm, though effective, leads to information loss. Solely using users' lifelong click behaviors doesn't provide a complete picture of their interests, leading to suboptimal performance. In our research, we introduce the Deep Group Interest Network (DGIN), an end-to-end method to model the user's entire behavior history. This includes all post-registration actions, such as clicks, cart additions, purchases, and more, providing a nuanced user understanding. We start by grouping the full range of behaviors using a relevant key (like item_id) to enhance efficiency. This process reduces the behavior length significantly, from O(10^4) to O(10^2). To mitigate the potential loss of information due to grouping, we incorporate two categories of group attributes. Within each group, we calculate statistical information on various heterogeneous behaviors (like behavior counts) and employ self-attention mechanisms to highlight unique behavior characteristics (like behavior type). Based on this reorganized behavior data, the user's interests are derived using the Transformer technique. Additionally, we identify a subset of behaviors that share the same item_id with the candidate item from the lifelong behavior sequence. The insights from this subset reveal the user's decision-making process related to the candidate item, improving prediction accuracy. Our comprehensive evaluation, both on industrial and public datasets, validates DGIN's efficacy and efficiency

AT4CTR: Auxiliary Match Tasks for Enhancing Click-Through Rate Prediction

Click-through rate (CTR) prediction is a vital task in industrial recommendation systems. Most existing methods focus on the network architecture design of the CTR model for better accuracy and suffer from the data sparsity problem. Especially in industrial recommendation systems, the widely applied negative sample down-sampling technique due to resource limitation worsens the problem, resulting in a decline in performance. In this paper, we propose \textbf{A}uxiliary Match \textbf{T}asks for enhancing \textbf{C}lick-\textbf{T}hrough \textbf{R}ate prediction accuracy (AT4CTR) by alleviating the data sparsity problem. Specifically, we design two match tasks inspired by collaborative filtering to enhance the relevance modeling between user and item. As the "click" action is a strong signal which indicates the user's preference towards the item directly, we make the first match task aim at pulling closer the representation between the user and the item regarding the positive samples. Since the user's past click behaviors can also be treated as the user him/herself, we apply the next item prediction as the second match task. For both the match tasks, we choose the InfoNCE as their loss function. The two match tasks can provide meaningful training signals to speed up the model's convergence and alleviate the data sparsity. We conduct extensive experiments on one public dataset and one large-scale industrial recommendation dataset. The result demonstrates the effectiveness of the proposed auxiliary match tasks. AT4CTR has been deployed in the real industrial advertising system and has gained remarkable revenue

A shorter loop in RouxY hepatojejunostomy reconstruction for choledochal cysts is equally effective: preliminary results of a prospective randomized study. J Pediatr Surg

Abstract Background: Conventionally, an adult's standard of a 40-cm loop is adopted in Roux-Y hepatojejunostomy (RYHJ) in choledochal cyst (CDC) in children, irrespective of patient size. The redundant length of the jejunal limb may lead to complications. We compared the outcome of an individualized short Roux loop with the standard loop length in RYHJ in children with CDC. Methods: Two hundred eighteen children with CDC undergoing laparoscopic RYHJ were prospectively randomized into 2 groups: (1) conventional group (CG; n = 108) where a standard 35-40 cm Roux-loop length was used regardless of the child's size and (2) short loop group (SLG; n = 110) in which the Roux-loop length was based on the distance between hepatic hilum and umbilicus. Ultrasonography, upper gastrointestinal contrast studies, and laboratory tests were conducted during the follow-up period. Results: The mean Roux-loop length of SLG was significantly shorter than that of CG (Student t test, P b .05). There was no significant difference between the 2 groups in age, operative blood loss, operative time, postoperative hospital stay, and duration of drainage. In CG, 2 of (1.8%) 108 patients developed Roux-loop obstruction, whereas none was detected in SLG (0%). Mild reflux was detected in 2 CG patients and 1 SLG patient 1 month postoperatively, all of which subsided 6 months later. No episodes of cholangitis were observed in either group. Conclusions: An individualized short Roux-loop length in RYHJ is as effective as the conventional Roux-loop length

The Decay Process of an {\alpha}-configuration Sunspot

The decay of sunspot plays a key role in magnetic flux transportation in solar active regions (ARs). To better understand the physical mechanism of the entire decay process of a sunspot, an {\alpha}-configuration sunspot in AR NOAA 12411 was studied. Based on the continuum intensity images and vector magnetic field data with stray light correction from Solar Dynamics Observatory/Helioseismic and Magnetic Imager, the area, vector magnetic field and magnetic flux in the umbra and penumbra are calculated with time, respectively. Our main results are as follows: (1) The decay curves of the sunspot area in its umbra, penumbra, and whole sunspot take the appearance of Gaussian profiles. The area decay rates of the umbra, penumbra and whole sunspot are -1.56 MSH/day, -12.61 MSH/day and -14.04 MSH/day, respectively; (2) With the decay of the sunspot, the total magnetic field strength and the vertical component of the penumbra increase, and the magnetic field of the penumbra becomes more vertical. Meanwhile, the total magnetic field strength and vertical magnetic field strength for the umbra decrease, and the inclination angle changes slightly with an average value of about 20{\deg}; (3) The magnetic flux decay curves of the sunspot in its umbra, penumbra, and whole sunspot exhibit quadratic patterns, their magnetic flux decay rates of the umbra, penumbra and whole sunspot are -9.84 * 10^19 Mx/day, -1.59 * 10^20 Mx/day and -2.60 * 10^20 Mx/day , respectively. The observation suggests that the penumbra may be transformed into the umbra, resulting in the increase of the average vertical magnetic field strength and the reduction of the inclination angle in the penumbra during the decay of the sunspot

Generation of Small 32P-Labeled Peptides as a Potential Approach to Colorectal Cancer Therapy

Cancers have been revealed to be extremely heterogenous in terms of the frequency and types of mutations present in cells from different malignant tumors. Thus, it is likely that uniform clinical treatment is not optimal for all patients, and that the development of individualized therapeutic regimens may be beneficial. We describe the generation of multiple, unique small peptides nine to thirty-four amino acids in length which, when labeled with the radioisotope 32P, bind with vastly differing efficiencies to cell lines derived from different colon adenocarcinomas. In addition, the most effective of these peptides permanently transfers the 32P radioisotope to colorectal cancer cellular proteins within two hours at a rate that is more than 150 times higher than in cell lines derived from other cancers or from the normal tissues tested. Currently, the only two FDA-approved radioimmunotherapeutic agents in use both employ antibodies directed against the B cell marker CD20 for the treatment of non-Hodgkin's lymphoma. By using the method described herein, large numbers of different 32P-labeled peptides can be readily produced and assayed against a broad spectrum of cancer types. This report proposes the development and use of 32P-labeled peptides as potential individualized peptide-binding therapies for the treatment of colon adenocarcinoma patients