# PolyTopix

In the last couple of years, I developed some (research) interest in recommendation algorithms and speech synthesis. My interests in these areas are geared towards developing an automated personalized news radio.

Almost all of us are interesting in consuming news. In this internet age, there is no dearth of news sources. Often we have too many sources. We tend to “read” news from several sources / news aggregators, spending several hours per week. Most of the time we are simply interested in the top and relevant headlines.

PolyTopix is my way of simplifying the process of consuming top and relevant news. The initial prototype is here. The website “reads” several news tweets (collected from different sources) and ordered based on a machine learning algorithm. Users can login and specify their individual interests (and zip code) to narrow down the news.

Try PolyTopix let me know your feedback. Here are some upcoming features :

• Automatically collect weather news (and local news) based on your location.
• Reading more details of most important news.
• News will be classified as exciting/sad/happy etc., (based on a machine learning algorithm) and read with the corresponding emotional voice.

Essentially PolyTopix is aimed towards a completely automated and personalized news radio, that can “read” news from across the world anytime with one click.

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It is well-known that an undirected graph is a partial 1-tree (i.e., a forest) if and only if it has no $K_3$ minor. We generalized this characterization to partial 1-DAGs. We proved that partial 1-DAGs are characterized by three forbidden directed minors, $K_3, N_4$ and $M_5$, shown in the following figure. We named the last two graphs as $N_4$ and $M_5$ because their bidirected edges resemble the letters N and M.